1.

論文

論文
Hirano, Akihiro ; Nakayama, Kenji
出版情報: 第26回信号処理シンポジウム講演論文集 = Proc. of 25th SIP Symposium.  pp.477-481,  2011-01-01.  電子情報通信学会 = The Institute of Electronics, Information and Communication Engineers
URL: http://hdl.handle.net/2297/35266
概要: This paper presents efficient implementa- tion of RLS-based adaptive filters with a large number of taps on nVIDIA GeForce graphics processing unit (GPU) and CUDA software development environment. Modification of the order and the combination of calcu- lations reduces the number of accesses to slow off-chip memory. Assigning tasks into multiple threads also takes memory access order into account. For a 4096-tap case, a GPU program is almost three times faster than a CPU program. 続きを見る
2.

論文

論文
Hirano, Akihiro ; Nakayama, Kenji
出版情報: 第27回信号処理シンポジウム講演論文集 = Proc. of 27th SIP Symposium.  pp.241-245,  2012-01-01.  電子情報通信学会 = The Institute of Electronics, Information and Communication Engineers
URL: http://hdl.handle.net/2297/35267
概要: This paper presents efficient implementa- tion of RLS-based adaptive filters with a large number of taps on nVIDIA GeForce graphics processing unit (GPU) and CUDA software development environment. Modification of the order and the combination of calcu- lations reduces the number of accesses to slow off-chip memory. Assigning tasks into multiple threads also takes memory access order into account. Multiple shader pro- cessor arrays are used to handle a large matrix. For a 8192-tap case, a GPU program is almost 30-times faster than a CPU program. Real-time processing is possible for an 8kHz-sampling and 512-tap case by us- ing 32 shader processors, which is only 25% of GeForce 8800GTS. 続きを見る
3.

論文

論文
Nakayama, Kenji
出版情報: IEEE transactions on circuits and systems.  31  pp.1002-1008,  1984-12-01.  Institute of Electrical and Electronics Engineers (IEEE)
URL: http://hdl.handle.net/2297/3949
概要: 金沢大学大学院自然科学研究科情報システム<br />金沢大学工学部<br />A simultaneous frequency- and time-domain approximation method for discrete-time filters is proposed. In the method, transfer function coefficients are divided into two subsets, X//1 and X//2, which are employed for optimizing a time response and a frequency response, respectively. Frequency and time responses are optimized through the iterative Chebyshev approximation method and a method of solving linear equations, respectively. At the rth iteration step, the maximum frequency response error, which appeared at the (r minus 1)th step, is minimized, and X//2**(**r** minus **1**) becomes X//2**(**r**). X//1**(**r**) is obtained from linear equations including X//2**(**r**) as a constant. The frequency response at the rth step is evaluated using the above obtained X//1**(**r**) and X//2**(**r**). This means the optimum time response is always guaranteed in the frequency-response approximation procedure. A design example of a symmetrical impulse response shows the new approach is more efficient than conventional methods from the filter order reduction viewpoint. 続きを見る
4.

論文

論文
Hara, Kazuyuki ; Nakayama, Kenji
出版情報: IEICE Trans. Fundamentals.  E81-A  pp.374-381,  1998-03-01. 
URL: http://hdl.handle.net/2297/5654
概要: 金沢大学大学院自然科学研究科知能情報・数理<br />A training data selection method is proposed for multilayer neural networks (MLNNs). This met hod selects a small number of the training data, which guarantee both generalization and fast training of the MLNNs applied to pattern classification. The generalization will be satisfied using the data locate close to the boundary of the pattern classes. However, if these data are only used in the training, convergence is slow. This phenomenon is analyzed in this paper. Therefore, in the proposed method, the MLNN is first trained using some number of the data, which are randomly selected (Step 1). The data, for which the output error is relatively large, are selected. Furthermore, they are paired with the nearest data belong to the different class. The newly selected data are further paired with the nearest data. Finally, pairs of the data, which locate close to the boundary, can be found. Using these pairs of the data, the MLNNs are further trained (Step 2). Since, there are some variations to combine Steps 1 and 2, the proposed method can be applied to both off-line and on-line training. The proposed method can reduce the number of the training data, at the same time, can hasten the training. Usefulness is confirmed through computer simulation. 続きを見る
5.

論文

論文
Nakayama, Kenji ; Kato, Takuo ; Katayama, Hiroshi
出版情報: IEEE&INNS Proc. IJCNN'93, Nagoya.  pp.2480-2483,  1993-10-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6822
6.

論文

論文
Nakayama, Kenji
出版情報: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  pp.1754-1757,  1998-04-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6858
概要: A bandlimited signal extrapolation algorithm is proposed. J. A. Cadzow's algorithm (1979) is modified to eliminate undesired outband spectra. An inverse filter stopband response is relaxed by adding small random numbers. A constrained heuristic optimization is suggested that can use arbitrary signal properties as constraints. Through numerical examples, it is shown how regularization techniques can improve SNR (signal-to-noise-ratio) by 20 dB. 続きを見る
7.

論文

論文
Keeni, Kanad ; Shimodaira, Hiroshi ; Nakayama, Kenji
出版情報: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR.  2  pp.600-603,  1997-08-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6795
概要: This paper presents an automatic coding scheme for representing the output layer of a neural network. Compared to local representation where the number of output unit is p, the number of output unit required for the proposed representation is close to log p. The output of seven different printers were used for evaluating the performance of the system. The proposed automatic representation gave the average recognition rate of 98.7% for 71 categories. 続きを見る
8.

論文

論文
Wang, Youhua ; Ikeda, Kazushi ; Nakayama, Kenji
出版情報: IEEE Proc. of ICASSP'98, Seattle.  pp.1713-1716,  1998-05-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6833
9.

論文

論文
Nakayama, Kenji ; Katayama, Hiroshi
出版情報: IEEE & INNS Proc. IJCNN'92, Baltimore.  Ⅰ  pp.888-893,  1992-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6846
10.

論文

論文
Ikeda, Kazushi ; Suzuki, Akihiro ; Nakayama, Kenji
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  pp.1896-1900,  1997-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6784
概要: The effects of the quantization of the parameters of a learning machine are discussed. The learning coefficient should be as small as possible for a better estimate of parameters. On the other hand, when the parameters are quantized, it should be relatively larger in order to avoid the paralysis of learning originated from the quantization. How to choose the learning coefficient is given in this paper from the statistical point of view. 続きを見る
11.

論文

論文
Horita, Akihide ; Nakayama, Kenji ; Hirano, Akihiro
出版情報: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).  4668 LNCS - I  pp.169-179,  2007-01-01.  Springer Verlag (Germany)
URL: http://hdl.handle.net/2297/9503
概要: 金沢大学大学院自然科学研究科情報システム<br />Feed-Forward (FF-) and Feed-Back (FB-) structures have been proposed for Blind Source Separati on (BSS). The FF-BSS systems have some degrees of freedom in the solution space, and signal distortion is likely to occur in convolutive mixtures. On the other hand, the FB-BSS structure does not cause signal distortion. However, it requires a condition on the propagation delays in the mixing process. In this paper, source separation performance in the FB-BSS is theoretically analyzed taking the propagation delays into account. Simulation is carried out by using white signals and speech signals as the signal sources. The FF-BSS system and the FB-BSS system are compared. Even though the FB-BSS can provide good separation performance, there exits some limitation on location of the signal sources and the sensors. © Springer-Verlag Berlin Heidelberg 2007. 続きを見る
12.

論文

論文
Hirano, Akihiro ; Nakayama, Kenji ; Arai, Shinya ; Deguchi, Masayuki
出版情報: IEICE transactions on fundamentals of electronics, communications and computer sciences.  E84-A  pp.414-421,  2001-02-01. 
URL: http://hdl.handle.net/2297/5653
概要: 金沢大学大学院自然科学研究科知能情報・数理
13.

論文

論文
Nakayama, Kenji ; Imai, Kunihiko
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  6  pp.3909-3914,  1994-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6836
概要: 金沢大学理工研究域電子情報学系<br />A neural demodulator is proposed for amplitude shift keying (ASK) signal. It has several important features compared with conventional linear methods. First, necessary functions for ASK demodulation, including wide-band noise rejection, pule waveform shaping, and decoding, can be embodied in a single neural network. This means these functions are not separately designed but unified in a learning and organizing process. Second, these functions can be self-organized through the learning. Supervised learning algorithms, such as the backpropagation algorithm, can be applied for this purpose. Finally, both wide-band noise rejection and a very sharp waveform response can be simultaneously achieved. It is very difficult to be done by linear filtering. Computer simulation demonstrates efficiency of the proposed method. 続きを見る
14.

論文

論文
Miyoshi, Seiji ; Nakayama, Kenji
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  3  pp.1913-1918,  1997-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6848
概要: In this paper, the geometric learning algorithm (GLA) is proposed for an elementary perceptron which includes a single output neuron. The GLA is a modified version of the affine projection algorithm (APA) for adaptive filters. The weights update vector is determined geometrically towards the intersection of the k hyperplanes which are perpendicular to patterns to be classified. k is the order of the GLA. In the case of the APA, the target of the coefficients update is a single point which corresponds to the best identification of the unknown system. On the other hand, in the case of the GLA, the target of the weights update is an area, in which all the given patterns are classified correctly. Thus, their convergence conditions are different. In this paper, the convergence condition of the 1st order GLA for 2 patterns is theoretically derived. The new concept `the angle of the solution area' is introduced. The computer simulation results support that this new concept is a good estimation of the convergence properties. 続きを見る
15.

論文

論文
Ma, Zhiqiang ; Nakayama, Kenji ; Yamamoto, G.
出版情報: Proc. IEEE ISCAS'92, San Diego.  pp.1203-1206,  1992-05-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6792
16.

論文

論文
Nakayama, Kenji ; Kuriki, Satoshi
出版情報: Proceedings - IEEE International Symposium on Circuits and Systems.  pp.1483-1486,  1985-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6837
概要: A simplified digital tuned-circuit extractor is proposed. An A/D converter and multipliers are not required. An A/D converter and multipliers are not required. The tuning frequency is determined only by a master clock. The tank circuit output noise is sufficiently suppressed by newly introduced error canceller. Although sampling frequency for the tank circuit is relatively low, the phase of the output signal is effectively detected. A computer simulation shows that phase adjusting for data sampling clock is stable. The proposed timing extractor is easily realized on digital integrated circuits. 続きを見る
17.

論文

論文
Nakayama, Kenji
出版情報: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  3  pp.1197-1200,  1981-04-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6791
概要: A new difference coefficient FIR digital filter is proposed. Its coefficient is obtained as the difference between the successive values of the original coefficients permuted in large magnitude sequence. It is effectively applied to every kind of filter responses. Computation complexity becomes about 18% and 13% for 99th and 299th order FIR filters, compared with direct FIR filter realization. 続きを見る
18.

論文

論文
Miyoshi, Seiji ; Nakayama, Kenji
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  2  pp.1291-1296,  1996-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6790
概要: 金沢大学理工研究域電子情報学系<br />In this paper, probabilistic memory capacity of recurrent neural networks(RNNs) is investigated. Th is probabilistic capacity is determined uniquely if the network architecture and the number of patterns to be memorized are fixed. It is independent from a learning method and the network dynamics. It provides the upper bound of the memory capacity by any learning algorithms in memorizing random patterns. It is assumed that the network consists of N units, which take two states. Thus, the total number of patterns is the Nth power of 2. The probabilities are obtained by discriminations whether the connection weights, which can store random M patterns at equilibrium states, exist or not. A theoretical way for this purpose is derived, and actual calculation is executed by the Monte Carlo method. The probabilistic memory capacity is very important in applying the RNNs to real fields, and in evaluating goodness of learning algorithms. As an example of a learning algorithm, the improved error correction learning is investigated, and its convergence probabilities are compared with the upper bound. A linear programming method can be effectively applied to this numerical analysis. 続きを見る
19.

論文

論文
Jansen, Boris ; Nakayama, Kenji
出版情報: Proceedings of the International Joint Conference on Neural Networks.  4  pp.2577-2582,  2005-08-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6796
概要: Nowadays, the integer prime-factorization problem finds its application often in modern cryptography. Artificial Neural Networks (ANNs) have been applied to the integer prime-factorization problem. A composed number N is applied to the ANNs, and one of its prime factors p is obtained as the output. Previously, neural networks dealing with the input and output data in a decimal format have been proposed. However, accuracy is not sufficient. In this paper, a neural network following a binary approach is proposed. The input N as well as the desired output p were expressed in a binary form. The proposed neural network is expected to be more stable, i.e. less sensitive to small errors in the network outputs. Simulations have been performed and the results are compared with the results reported in the previous study. The number of required search times for the true prime number can be well reduced. Furthermore, the probability density function of the training patterns is investigated and the need for different data creation and/or selection techniques is shown. © 2005 IEEE. 続きを見る
20.

論文

論文
Nakayama, Kenji ; Ikehara, Keisuke
出版情報: IEEE&INNS, Proc. IJCNN'92, Beijing.  pp.Ⅱ53-Ⅱ58,  1992-11-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6819
21.

論文

論文
Nakayama, Kenji ; Kimura, Yoshinori ; Katayama, Hiroshi
出版情報: Proceedings of the International Joint Conference on Neural Networks.  2  pp.1247-1250,  1993-10-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6789
概要: In this paper, quantization level increase in human face images using a multilayer neural network (NN) is investigated. Basically speaking, it is impossible to increase quality without any other information. However, when images are limited to some category, image restoration could be possible, based on the common properties in this category. The multilayer NN is trained using human face images of 32テ・2 pixels with 8-levels as the input data, and 256-level images as the targets. The standard back-propagation (BP) algorithm is employed. 20, 40 and 100 training data are examined. By increasing the training data, a general function of regenerating missing information can be achieved. The internal structure of the trained NN is analyzed using some special input images. As a result, it has been confirmed that the NN regards the input image as the human face, and extracts features of the face. The input image is transformed using these features and the common properties of the training data, extracted and held on the connection weights, to the human face image. 続きを見る
22.

論文

論文
Nakayama, Kenji ; Hirano, Akihiro ; Katoh, Shinya ; Yamamoto, Tadashi ; Nakanishi, Kenichi ; Sawada, Manabu
出版情報: Proceedings of the International Joint Conference on Neural Networks.  2  pp.1373-1378,  2002-05-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6806
概要: In training neural networks, it is important to reduce input variables for saving memory, reducing network size, and ach ieving fast training. This paper proposes two kinds of selecting methods for useful input variables. One of them is to use information of connection weights after training. If a sum of absolute value of the connection weights related to the input node is large, then this input variable is selected. In some case, only positive connection weights are taken into account. The other method is based on correlation coefficients among the input variables. If a time series of the input variable can be obtained by amplifying and shifting that of another input variable, then the former can be absorbed in the latter. These analysis methods are applied to predicting cutting error caused by thermal expansion and compression in machine tools. The input variables are reduced from 32 points to 16 points, while maintaining good prediction within 6 ホシm, which can be applicable to real machine tools. 続きを見る
23.

論文

論文
Kuraishi, Yoshiaki ; Makabe, Takayoshi ; Nakayama, Kenji
出版情報: IEEE Journal of Solid-State Circuits.  17  pp.1039-1044,  1982-12-01.  Institute of Electrical and Electronics Engineers (IEEE)
URL: http://hdl.handle.net/2297/3951
概要: 金沢大学大学院自然科学研究科情報システム<br />金沢大学工学部<br />This paper presents a fully integrated analog front-end LSI chip which is an inte rface system between digital signal processors and existing analog telecommunication networks. The developed analog LSI chip includes many high level function blocks such as A/D and D/A converters with 11 bit resolution, various kinds of SCF's, an agc circuit, an external control level adjuster, a carrier detector, and a zero crossing detector. Design techniques employed are mainly directed toward circuit size reductions. The LSI chip is fabricated in a 5 mu m line double polysilicon gate NMOS process. Chip size is 7. 14 multiplied by 6. 51 mm. The circuit operates on plus or minus 5 v power supplies. Typical power consumption is 270 mw. By using this analog front-end LSI chip and a digital signal processor, modern systems can be successfully constructed in a compact size. 続きを見る
24.

論文

論文
Nakayama, Kenji ; Hirano, Akihiro ; Dejima, Yasuhiro
出版情報: IEEE Proc. The 47th International Midwest Symposium on Circuits and Systems (MWSCAS2004), Hiroshima, Japan.  3  pp.III_207-III_210,  2004-09-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6816
概要: This paper analyzes signal separation and distortion in a feedforward blind source separation (BSS) applied to convolutive mixture environment. In the BSS learning, a separation block is adjusted so as to make the output signals statistically independent. One direction for this adjustment is to extract only one signal source at a single output. The other direction is to make the output signal spectra white. The second direction causes signal distortion and conflicts with the first direction. This confliction prevent signal separation. These relations are also dependent on a length of the impulse responses in the mixture and the filter length in the separation block. These properties are theoretically analyzed and are investigated through simulations using the white signal sources and the speech signal sources. 続きを見る
25.

論文

論文
Xu, Q. ; Nakayama, Kenji
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  3  pp.1954-1959,  1997-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6813
概要: This paper investigates some possible problems of Cascade Correlation algorithm, one of which is the zigzag output mapping caused by weight-illgrowth of the adding hidden unit. Without doubt, it could lead to deteriorate the generalization, especially for regression problems. To solve this problem, we combine Cascade Correlation algorithm with regularization theory. In addition, some new regularization terms are proposed in light of special cascade structure. Simulation has shown that regularization indeed smooth the zigzag out-put, so that the generalization is improved, especially for functional approximation. 続きを見る
26.

論文

論文
Nakayama, Kenji ; Chigawa, Yasuhide ; Hasegawa, Osamu
出版情報: IEEE&INNS Proc. IJCNN'92, Baltimore.  Ⅳ  pp.235-240,  1992-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6799
27.

論文

論文
Nakayama, Kenji ; Kato, Takuo
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  pp.4237-4242,  1994-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6821
28.

論文

論文
Tokui, N. ; Nakayama, Kenji ; Hirano, Akihiro
出版情報: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  6  pp.349-352,  2003-01-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6812
概要: In order to achieve fast convergence and less computation for adaptive filters, a joint method combining a whitening process and the NLMS algorithm is a hopeful approach. However, updating the filter coefficients is not synchronized with the reflection coefficient updating resulting in unstable behavior. We analyzed effects of this, and proposed the Synchronized Learning Algorithm to solve this problem. Asynchronous error between them is removed, and fast convergence and small residual error were obtained. This algorithm, however, requires O(ML) computations, where M is an adaptive filter length, and L is a lattice predictor length. It is still large compared with the NLMS algorithm. In order to achieve less computation while the fast convergence is maintained, a block implementation method is proposed. The reflection coefficients are updated at some period, and are fixed during this interval. The proposed block implementation can be effectively applied to parallel form adaptive filters, such as sub-band adaptive filters. Simulation using speech signal shows that a learning curve of the proposed block implementation a little slower than the our original algorithm, but can save the computational complexity. 続きを見る
29.

論文

論文
Hirano, Akihiro ; Nakayama, Kenji ; Ushimaru, S.
出版情報: Proc. 2003 IEEE International Symposium on Intellogent Signal Processing and Communication Systems (ISPACS2003), Awajishima, Japan.  pp.367-370,  2003-12-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6802
30.

論文

論文
Yukawa, Akira ; Maruta, Rikio ; Nakayama, Kenji
出版情報: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  pp.1400-1403,  1985-03-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6817
31.

論文

論文
Nakayama, Kenji ; Iwata, Atsushi ; Yanagisawa, Takeshi
出版情報: IEICE transactions on fundamentals of electronics, communications and computer sciences.  E71-E  pp.1177-1188,  1998-12-01. 
URL: http://hdl.handle.net/2297/5643
概要: 金沢大学大学院自然科学研究科情報システム
32.

論文

論文
Hibino, Masao ; Nakayama, Kenji ; Mizukami, Toshihiko
出版情報: Proc. IEEE ISCAS'79, Tokyo.  pp.368-369,  1979-07-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6803
33.

論文

論文
Ohnishi, K. ; Nakayama, Kenji
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  pp.1933-1937,  1996-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6835
概要: 金沢大学理工研究域電子情報学系<br />A neural demodulator is proposed for quadrature amplitude modulation (QAM) signals. It has several important features compared with conventional linear methods. First, necessary functions for the QAM demodulation, including wide-band noise rejection, pulse waveform shaping, and decoding, can be embedded in a single neural network. This means that these functions are not separately designed but are unified in a learning process. Second, these functions can be self-organized through the learning. Supervised learning algorithms, such as the back-propagation algorithm, can be applied for this purpose. Finally, both wide-band noise rejection and a very sharp waveform response can be simultaneously achieved. It is very difficult to be done by linear filtering. Computer simulation demonstrates efficiency of the proposed method. 続きを見る
34.

論文

論文
Wang, Youhua ; Terada, Yasuhiro ; Matsui, Minoru ; Iida, Kazuhiro ; Nakayama, Kenji
出版情報: IEEE Proc. ICASSP'2000, Istanbul, Turkey.  pp.VI-3674-VI-3677,  2000-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6805
35.

論文

論文
Hara, Kazuyuki ; Nakayama, Kenji
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  1  pp.436-441,  1996-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6788
概要: 金沢大学理工研究域電子情報学系<br />A training data reduction method for a multilayer neural network (MLNN) is proposed in this paper. This method reduce the data by selecting the minimum number of training data that guarantee generality of the MLNN. For this purpose, two methods are used. One of them is a pairing method which selects the training data by finding the nearest data of the different classes. Data along the class boundary in data space can be selected. The other method is a training method, which used a semi-optimum MLNN in a training process. Since the MLNN classify data based on the distance from the network boundary, the selected data can locate close to the class boundary. So, if the semi-optimum MLNN did not select data from class boundary, pairing method can select them. The proposed methods can be applied to both off-line training and on-line training. The proposed method is also investigated through computer simulation. 続きを見る
36.

論文

論文
Hara, Kazuyuki ; Nakayama, Kenji
出版情報: IEEE International Conference on Neural Networks - Conference Proceedings.  1  pp.600-605,  1995-11-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6787
概要: Signal classification performance using multilayer neural network (MLNN) and the conventional signal processing methods are theoretically compared under the limited observation period and computational load. The signals with N samples are classified based on frequency components. The comparison is carried out based on degree of freedom the signal detection regions in an N-dimensional signal space. As a result, the MLNN has higher degree of freedom, and can provide more flexible performance for classifying the signals than the conventional methods. This analysis is further investigated throught computer simulations. Multi-frequency signals and the real application, a dial tone receiver, are taken into account. As a result, the MLNN can provide much higher accuracy than the conventional signal processing methods. 続きを見る
37.

論文

論文
Nakayama, Kenji ; Katou, Haruo ; Hirano, Akihiro
出版情報: Proc.IEEE, ISPACS2006, Yonago, Japan.  pp.459-462,  2006-12-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6849
38.

論文

論文
Nakayama, Kenji ; Sato, Yayoi ; Kuraishi, Yoshiaki
出版情報: IEEE transactions on circuits and systems.  CAS-32  pp.759-766,  1985-08-01.  Institute of Electrical and Electronics Engineers (IEEE)
URL: http://hdl.handle.net/2297/3948
概要: 金沢大学大学院自然科学研究科情報システム<br />金沢大学工学部<br />Design techniques are described for a switched capacitor adaptive line equalizer which is applied to high-speed (200 kb/s) digital transmission over analog subscriber loops. An equalizer transfer function is approximated so as to minimize intersymbol interference of an isolated pulse response. Optimum pole-zero location, which is suited to line characteristics in a wide frequency band, is also discussed. In order to attain high accuracy capacitor ratios using a small unit capacitor, capacitor values are rounded off into equivalent integer values, and are discretely optimized using pole-zero deviation as an error criterion. The equalizer has a finite number of frequency responses which correspond to line lengths. Gain and delay time differences between the adjoining step responses are compressed. The switched capacitor line equalizer was fabricated using 3- mu m CMOS technology. Measured data were very close to designed performances. 続きを見る
39.

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Nakayama, Kenji ; Mizukami, Toshihiko
出版情報: IEEE transactions on circuits and systems.  29  pp.23-24,  1982-01-01.  Institute of Electrical and Electronics Engineers (IEEE)
URL: http://hdl.handle.net/2297/3955
概要: 金沢大学大学院自然科学研究科情報システム<br />金沢大学工学部<br />A new infinite impulse response (IIR) Nyquist filter with zero intersymbol interf erence is proposed. The necessary and sufficient conditions for the transfer function are obtained. The proposed IIR Nyquist filter requires only frequency-domain optimization. Multistep optimization, using the iterative Chebyshev approximation, is proposed. This method is able to design a new kind of IIR Nyquist filter with the minimum order. Numerical examples for 30- and 15-percent rolloff rates are illustrated. From these examples, it is confirmed that the IIR approach can reduce the filter order and hardware size, compared with the conventional finite impulse response (FIR) Nyquist filters. Its efficiency becomes marked for high Q Nyquist filters. 続きを見る
40.

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論文
Nakayama, Kenji
出版情報: IEICE transactions on fundamentals of electronics, communications and computer sciences.  E70  pp.735-743,  1987-08-01. 
URL: http://hdl.handle.net/2297/5644
概要: 金沢大学大学院自然科学研究科情報システム<br />This paper proposes a new discrete optimization method which is mainly directed toward saving computing time for high-order FIR filters. A transfer functions first approximated in a cascade form of a low-order function W(z) with pre-rounded coefficients and a high-order function F(z) with infinite precision coefficients. Rounded F(z) coefficients are discretely optimized to minimize the mean square error of the amplitude response. The roundoff error spectrum is shaped to be suppressed by a weighting function W(z). In order to save computing time, the error is equivalently evaluated in a time domain, and the F(z) coefficients are divided into small groups in the discrete optimization procedure. Design examples for 200 tap FIR filters demonstrate practical usefulness. 続きを見る
41.

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論文
Horita, Akihide ; Nakayama, Kenji ; Hirano, Akihiro ; Dejima, Yasuhiro
出版情報: Proceedings of the International Joint Conference on Neural Networks.  2  pp.1257-1262,  2005-08-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6815
概要: Source separation and signal distortion in three kinds of BSSs with convolutive mixture are analyzed. They include a fee dforward BSS, trained in the time domain and in the frequency domain, and a feedback BSS, trained in the time domain. First, an evaluation measure of signal distortion is discussed. Second, conditions for source separation and distortion free are derived. Based on these conditions, source separation and signal distortion are analyzed. The feedforward BSS has some degree of freedom, and the output spectrum can be changed. The feedforward BSS, trained in the frequency domain, has weighting effect, which can suppress signal distortion. This weighting is, however, effective only when the source spectra are similar to each other. Since, the feedforward BSS, trained in the time domain, does not have any constraints on signal distortion free, its output signals can be easily distorted. A new learning algorithm with a distortion free constraint is proposed. On the other hand, the feedback BSS can satisfy both source separation and distortion free conditions simultaneously. Simulation results support the theoretical analysis. © 2005 IEEE. 続きを見る
42.

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Miyoshi, Seiji ; Ikeda, Kazushi ; Nakayama, Kenji
出版情報: IEEE&INNS Proc. of IJCNN'98, Anchorage.  pp.2340-2345,  1998-05-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6807
43.

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論文
Nakayama, Kenji
出版情報: Proc.IEEE ICASSP'82, Paris.  pp.484-487,  1982-01-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6851
44.

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論文
Hirano, Akihiro ; Nakayama, Kenji ; Watanabe, Kazunobu
出版情報: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.  2  pp.861-864,  1999-03-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6809
概要: This paper presents convergence characteristics of stereophonic echo cancellers with pre-processing. The convergence analysis of the averaged tap-weights show that the convergence characteristics depends on the relation between the impulse response in the far-end room and the changes of the pre-processing filters. Examining the uniqueness of the solution in the frequency domain leads us to the same relation. Computer simulation results show the validity of these analyses. 続きを見る
45.

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論文
Nakayama, Kenji ; Ohsugi, M.
出版情報: IEEE&INNS Proc. of IJCNN'98, Anchorage.  pp.2253-2257,  1998-05-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6828
46.

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論文
Nakayama, Kenji ; Hirano, Akihiro ; Sakaguchi, Hiroaki
出版情報: Proc. 2003 IEEE International Symposium on Intellogent Signal Processing and Communication Systems (ISPACS2003), Awajishima, Japan.  pp.375-378,  2003-12-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6859
47.

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論文
Nakayama, Kenji ; Hirano, Akihiro ; Nishiwaki, Takayuki
出版情報: Proceedings of the International Joint Conference on Neural Networks.  3  pp.1856-1861,  2003-07-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6855
概要: A network structure and its learning algorithm have been proposed for blind source separation applied to nonlinear mixtures. The network has a cascade form consists of a source separation block and a linearization block in this order. The conventional learning algorithm is employed for the separation block. A new learning algorithm is proposed for the linearization block assuming 2nd-order nonlinearity. After, source separation, the outputs include the nonlinear components for the same signal source. This nonlinearity is suppressed through the linearization block. Parameters in this block are iteratively adjusted based on a process of solving a 2nd-order equation of a single variable. Simulation results, using 2-channel speech signals and an instantaneous nonlinear mixing process, show good separation performance. 続きを見る
48.

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論文
Nakayama, Kenji ; Mitsutani, N.
出版情報: Proc. IEEE&INNS IJCNN'91, Seattle.  II  pp.A-914-,  1991-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6820
概要: Summary form only given. A novel adaptive threshold method is proposed for an associative memory using a mutually connec ted neural network. Computer simulation was carried out, using 51 and 153 patterns, which appear on a keyboard. The neural network has 16 × 16 = 256 units and full connections. Results demonstrate that dramatic improvements in memory capacity and association rates can be achieved. For example, an association rate for 51 patterns with 40 noises has been increased from 12.2% to 97.7%, compared with a single threshold method. 続きを見る
49.

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論文
Nakayama, Kenji ; Mizukami, T.
出版情報: Proceedings - IEEE International Symposium on Circuits and Systems.  pp.317-320,  1985-06-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6834
概要: A new approach for low-bit-rate coding is proposed. Numerical evaluation for the bit-rate compression ratio and SNR shows the proposed method provides good performance compared with conventional linear PCM coding. Furthermore, since the predictor in the coder does not utilize any of the input signal statistics, this method can be applied for both speech and music coding. 続きを見る
50.

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Hara, Kazuyuki ; Nakayama, Kenji
出版情報: IEEE&INNS Proc. IJCNN'93, Nagoya.  1  pp.601-604,  1993-10-01.  IEEE(Institute of Electrical and Electronics Engineers)
URL: http://hdl.handle.net/2297/6811
概要: Frequency analysis capability of multilayer neural networks, trained by back-propagation (BP) algorithm is investigated. Multi-frequency signal classification is taken into account for this purpose. The number of frequency sets, that is signal groups, is 2approx.5, and the number of frequencies included in a signal group is 3approx.5. The frequencies are alternately located among the signal groups. Through computer simulation, it has been confirmed that the neural network has very high resolution. Classification rates are about 99.5% for training signals, and 99.0% for untraining signals. The results are compared with conventional methods, including Euclidean distance with accuracy of about 65%, Fourier transform with accuracy of about 10approx.30%, and using very high-Q filters with a huge number of computations. The neural network requires only the same number of inner products as the hidden units. Frequency sensitivity and robustness for the random noise are studied. The networks show high frequency sensitivity, namely, the networks have high frequency resolution. Random noise are added to the multi-frequency signals to investigate how does the network cancel uncorrelated noise among the signals. By increasing the number of samples, or training signals, effects of random noise can be cancelled. 続きを見る