1.

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
2.

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
3.

論文

論文
Wang, Youhua ; Ikeda, Kazushi ; Nakayama, Kenji
出版情報: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing.  Proceedings 3  pp.1713-1716,  1998-01-01.  IEEE
URL: http://hdl.handle.net/2297/3943
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 />The numerical property of an adaptive filter algorithm is the most important prob lem in practical applications. Most fast adaptive filter algorithms have the numerical instability problem and the fast Newton transversal filter (FNTF) algorithms are no exception. In this paper, we propose a numerically stable fast Newton type adaptive filter algorithm. Two problems are dealt with in the paper. First, we derive the proposed algorithm from the order-update fast least squares (FLS) algorithm. This derivation is direct and simple to understand. Second, we give the stability analysis using a linear time-variant state-space method. The transition matrix of the proposed algorithm is given. The eigenvalues of the ensemble average of the transition matrix are shown to be asymptotically all less than unity. This results in a much improved numerical performance compared with the FNTF algorithms. The computer simulations implemented by using a finite-precision arithmetic have confirmed the validity of our analysis. 続きを見る
4.

論文

論文
Wang, Youhua ; Nakayama, Kenji
出版情報: IEICE transactions on fundamentals of electronics, communications and computer sciences.  E-80A  pp.745-752,  1997-04-01. 
URL: http://hdl.handle.net/2297/5650
概要: 金沢大学大学院自然科学研究科情報システム<br />The numerical properties of the recursive least squares (RLS) algorithm and its fast versions have been extensively studied. However, very few investigations are reported concerning the numerical behavior of the predictor based least squares (PLS) algorithms that provide the same least squares solutions as the RLS algorithm. This paper presents a comparative study on the numerical performances of the RLS and the backward PLS (BPLS) algorithms. Theoretical analysis of three main instability sources reported in the literature, including the over-range of the conversion factor, the loss of symmetry and the loss of positive definiteness of the inverse correlation matrix, has been done under a finite-precision arithmetic. Simulation results have confirmed the validity of our analysis. The results show that three main instability sources encountered in the RLS algorithm do not exist in the BPLS algorithm. Consequently, the BPLS algorithm provides a much more stable and robust numerical performance compared with the RLS algorithm. 続きを見る
5.

論文

論文
Wang, Youhua ; Nakayama, Kenji ; Ma, Zhiqiang
出版情報: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences.  E78-A  pp.845-853,  1995-07-01.  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences = 電子情報通信学会
URL: http://hdl.handle.net/2297/18370
概要: 金沢大学理工研究域 電子情報学系<br />This paper presents a new structure for noise and echo cancelers based on a combined fast adaptive algorithm. The main purpose of the new structure is to detect both the double-talk and the unknown path change. This goal is accomplished by using two adaptive filters. A main adaptive filter Fn, adjusted only in the non-double-talk period by the normalized LMS algorithm, is used for providing the canceler output. An auxiliary adaptive filter Ff, adjusted by the fast RLS algorithm, is used for detecting the double-talk and obtaining a near optimum tap-weight vector for Fn in the initialization period and whenever the unknown path has a sudden or fast change. The proposed structure is examined through computer simulation on a noise cancellation problem. Good cancellation performance and stable operation are obtained when signal is a speech corrupted by a white noise, a colored noise and another speech signal. Simulation results also show that the proposed structure is capable of distinguishing the near-end signal from the noise path change and quickly tracking this change. 続きを見る
6.

論文

論文
Ikeda, Kazushi ; Wang, Youhua ; Nakayama, Kenji
出版情報: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences.  E80-A  pp.2286-2290,  1997-11-25.  IEICE 電子情報通信学会
URL: http://hdl.handle.net/2297/24657
概要: 金沢大学理工研究域電子情報学系<br />The numerical property of the recursive least squares (RLS) algorithm has been extensively studied. However, very few investigations are reported concerning the numerical behavior of the predictor-based least squares (PLS) algorithms which provide the same least squares solutions as the RLS algorithm. In Ref. [9], we gave a comparative study on the numerical performances of the RLS and the backward PLS (BPLS) algorithms. It was shown that the numerical property of the BPLS algorithm is much superior to that of the RLS algorithm under a finite-precision arithmetic because several main instability sources encountered in the RLS algorithm do not appear in the BPLS algorithm. This paper theoretically shows the stability of the BPLS algorithm by error propagation analysis. Since the time-variant nature of the BPLS algorithm, we prove the stability of the BPLS algorithm by using the method as shown in Ref. [6]. The expectation of the transition matrix in the BPLS algorithm is analyzed and its eigenvalues are shown to have values within the unit circle. Therefore we can say that the BPLS algorithm is numerically stable. 続きを見る
7.

論文

論文
Wang, Youhua ; Nakayama, Kenji
出版情報: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences.  E77-A  pp.247-256,  1994-06-01. 
URL: http://hdl.handle.net/2297/18376
概要: 金沢大学理工研究域 電子情報学系<br />This paper proposes a new combined fast algorithm for transversal adaptive filters. The fast trans versal filter (FTF) algorithm and the normalized LMS (NLMS) are combined in the following way. In the initialization period, the FTF is used to obtain fast convergence. After converging, the algorithm is switched to the NLMS algorithm because the FTF cannot be used for a long time due to its numerical instability. Nonstationary environment, that is, time varying unknown system for instance, is classified into three categories: slow time varying, fast time varying and sudden time varying systems. The NLMS algorithm is applied to the first situation. In the latter two cases, however, the NLMS algorithm cannot provide a good performance. So, the FTF algorithm is selected. Switching between the two algorithms is automatically controlled by using the difference of the MSE sequence. If the difference exceeds a threshold, then the FTF is selected. Other wise, the NLMS is selected. Compared with the RLS algorithm, the proposed combined algorithm needs less computation, while maintaining the same performance. Furthermore, compared with the FTF algorithm, it provides numerically stable operation. 続きを見る
8.

論文

論文
Wang, Youhua ; Ma, Zhiqiang ; Nakayama, Kenji
出版情報: Proceedings of the ISPACS'93, Sendai.  pp.14-19,  1993-10-01.  International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) / IEEE
URL: http://hdl.handle.net/2297/11894
9.

論文

論文
Wang, Youhua ; Nakayama, Kenji
出版情報: IEICE transactions on fundamentals of electronics, communications and computer.  E78-A  pp.999-1003,  1995-08-01.  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences = 電子情報通信学会
URL: http://hdl.handle.net/2297/18369
概要: 金沢大学理工研究域 電子情報学系<br />In this letter, we introduce a predictor based least square (PLS) algorithm. By involving both ord er- and time-update recursions, the PLS algorithm is found to have a more stable performance compared with the stable version (Version II) of the RLS algorithm shown in Ref. [1]. Nevertheless, the computational requirement is about 50% of that of the RLS algorithm. As an application, the PLS algorithm can be applied to the fast newton transversal filters (FNTF) [2]. The FNTF algorithms suffer from the numerical instability problem if the quantities used for extending the gain vector are computed by using the fast RLS algorithms. By combing the PLS and the FNTF algorithms, we obtain a much more stable performance and a simple algorithm formulation. 続きを見る