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S. Kinjo - One of the best experts on this subject based on the ideXlab platform.

  • A subband adaptive Filter with the statistically optimum Analysis Filter bank
    IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1998
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters using Filter banks have shown degradation in their performance because of the nonideal nature of Analysis Filters. For this problem, we propose two kinds of subband adaptive digital Filters. The first one has the statistically optimum Analysis Filter bank which minimizes error signals. This first method, however, needs some statistics of the signals; therefore, we propose another type of subband adaptive digital Filter which requires no a priori knowledge of the statistics regarding the signals. Computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filters.

  • A subband adaptive Filter with a variable Analysis Filter bank
    Conference Record of The Twenty-Ninth Asilomar Conference on Signals Systems and Computers, 1
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters (ADFs) using Filter banks have shown performance degradation because of the non-ideal nature of the Analysis Filters. For this problem, we propose a new class of subband ADFs which has two kinds of Analysis Filter banks. We first claim that subband ADFs with the optimum Analysis Filter bank, which can minimize the least squares error at each bin, can be designed in accordance with the statistics of the signals. We also propose a practical type of subband ADF which requires no a priori knowledge of the the signals statistics. Several computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filters.

  • ICASSP - A subband adaptive Filter with a variable Analysis Filter bank
    1996 IEEE International Conference on Acoustics Speech and Signal Processing Conference Proceedings, 1
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters (ADFs) using Filter banks have shown degradation in its performance because of the non-ideal nature of Analysis Filters. For this problem, we propose a new class of subband ADF which has two kinds of Analysis Filter banks. We first claim that subband ADFs with the optimum Analysis Filter bank, which can minimize the least squares error at each bin, can be designed in accordance with the statistics of the signals. We also propose a practical type of subband ADF which requires no a priori knowledge of the statistics regarding the signals. Several computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filter.

  • ICASSP - A subband adaptive Filter with the optimum Analysis Filter bank
    1995 International Conference on Acoustics Speech and Signal Processing, 1
    Co-Authors: Hiroshi Ochi, Yoshito Higa, S. Kinjo
    Abstract:

    Conventional subband ADFs (adaptive digital Filters) using Filter banks have shown degradation in performance because of the non-ideal nature of Filters. For this problem, we propose a new type of subband ADF incorporating two types of Analysis Filter bank. In this paper, we show that we can design the optimum Filter bank which minimizes the LMSE (least mean squared error). In other words, we can design a subband ADF with less MSE than that of conventional subband ADFs.

  • A subband adaptive Filter with two types of Analysis Filter bank
    Proceedings of 1994 28th Asilomar Conference on Signals Systems and Computers, 1
    Co-Authors: Hiroshi Ochi, Yoshito Higa, S. Kinjo
    Abstract:

    Conventional subband ADFs (adaptive digital Filters) using Filter banks have shown degradation in performance because of the non-ideal nature of Filters. For this problem, we propose a new type of subband ADF incorporating two types of analyses Filter bank. We show that we can design the optimum Filter bank which minimizes the LMSE (least mean squared error). In other words, we can design a subband ADF with less MSE than that of conventional subband ADFs. >

Alberto Leon-garcia - One of the best experts on this subject based on the ideXlab platform.

  • Subband decomposition of signals with generalized sampling
    IEEE Transactions on Signal Processing, 1993
    Co-Authors: Masoud R. K. Khansari, Alberto Leon-garcia
    Abstract:

    The authors generalize down and up-sampling operations by proposing block sampling. Perfect reconstruction conditions for two-band subband coding with block sampling are derived. By generalizing the sampling operation, new degrees of freedom are introduced and as a result, Filter banks which were not previously possible become possible. Generalized down-sampler introduces different aliasing components than that of the traditional down-sampler. This can be used to ease some the requirements of the Filter bank design problem. A constructive sampling method is proposed so that coprimeness of the transfer functions of the Analysis Filter banks is not only a necessary but also sufficient condition for perfect reconstruction. The results are extended to the case where the Filter banks are linear periodically time-varying. The multichannel case is analyzed and the relation between unimodular matrices and perfect reconstruction Filter banks is discussed. >

  • ICASSP (3) - Multidimensional perfect reconstruction Filter banks with generalized subsampling
    IEEE International Conference on Acoustics Speech and Signal Processing, 1993
    Co-Authors: Masoud R. K. Khansari, Alberto Leon-garcia
    Abstract:

    It is shown how a class of nonlattice sampling grids can be analyzed, and required PR (perfect reconstruction) conditions for the two-band subband decomposition are derived. This is done through the generalization of the sampling operation involved in the multirate systems. By generalizing sub/up-sampling operations, new degrees of freedom are introduced which can be used to facilitate the Filter design problem. It can be shown that for a specific Analysis Filter bank, PR might be possible with one sampling strategy and not with the other ones. Therefore, the design of Filter banks should be considered as a joint sampling/Filter design problem. >

  • Perfect reconstruction conditions for subband decomposition with generalized subsampling
    Visual Communications and Image Processing '92, 1992
    Co-Authors: Masoud R. K. Khansari, Alberto Leon-garcia
    Abstract:

    The operation of block sub-sampling and up-sampling are defined. Perfect reconstruction conditions for 2-band subband coding using these block sampling operations are then derived. It is shown that if the Analysis Filter banks do not have a common zero, there always exists a subsampling strategy such that perfect reconstruction is possible. The results are then generalized to the case of the periodically time-varying Filter banks.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

D L Duttweiler - One of the best experts on this subject based on the ideXlab platform.

  • avoiding slow band edge convergence in subband echo cancelers
    IEEE Transactions on Signal Processing, 2001
    Co-Authors: D L Duttweiler
    Abstract:

    Subband echo cancelers decompose their input signals into frequency bands and then do echo canceling on a per-band basis. Such structures have both computational and algorithmic advantages over conventional full-band structures. However, many implementations have been found to suffer from slow convergence at band edges, that is, at frequencies carried roughly equally by two adjacent subbands. A poorly conditioned correlation matrix with eigenvalues approaching zero is generally cited as the culprit. One possible solution to the poor band-edge convergence problem is a scheme dubbed postFiltering by Morgan (1995) and De Leon (1995). Under postFiltering, the slowly converging eigenmodes continue to be excited, but their energy is removed from the final output. An alternative solution developed here makes the subband Analysis Filter for the reference signal slightly broader in spectrum than the Analysis Filter for the echo. With unequal Analysis Filtering, it is possible to avoid eliciting the bad eigenmodes in the first place. There are important practical advantages for unequal Analysis Filtering. Extreme care must be exercised in Filter design. However, given a proper understanding of requirements, it is possible to synthesize reasonable-length FIR Filters with entirely satisfactory performance.

  • Avoiding Slow Band-Edge Convergence in Subband
    2001
    Co-Authors: Echo Cancelers, D L Duttweiler
    Abstract:

    Subband echo cancelers decompose their input signals into frequency bands and then do echo canceling on a per-band basis. Such structures have both computational and algorithmic advantages over conventional full-band structures. However, many implementations have been found to suffer from slow convergence at band edges, that is, at frequencies carried roughly equally by two adjacent subbands. A poorly conditioned correlation matrix with eigenvalues approaching zero is generally cited as the culprit. One possible solution to the poor band-edge convergence problem is a scheme dubbed postFiltering by Morgan and De Leon. Under postFiltering, the slowly converging eigenmodes continue to be excited, but their energy is removed from the final output. An alternative solution developed here makes the subband Analysis Filter for the reference signal slightly broader in spectrum than the Analysis Filter for the echo. With unequal Analysis Filtering, it is possible to avoid exciting the bad eigenmodes in the first place. There are important practical advantages for unequal Analysis Filtering. Extreme care must be exercised in Filter design. However, given a proper understanding of requirements, it is possible to synthe- size reasonable-length FIR Filters with entirely satisfactory perfor- mance.

Yoshito Higa - One of the best experts on this subject based on the ideXlab platform.

  • A subband adaptive Filter with the statistically optimum Analysis Filter bank
    IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1998
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters using Filter banks have shown degradation in their performance because of the nonideal nature of Analysis Filters. For this problem, we propose two kinds of subband adaptive digital Filters. The first one has the statistically optimum Analysis Filter bank which minimizes error signals. This first method, however, needs some statistics of the signals; therefore, we propose another type of subband adaptive digital Filter which requires no a priori knowledge of the statistics regarding the signals. Computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filters.

  • A subband adaptive Filter with a variable Analysis Filter bank
    Conference Record of The Twenty-Ninth Asilomar Conference on Signals Systems and Computers, 1
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters (ADFs) using Filter banks have shown performance degradation because of the non-ideal nature of the Analysis Filters. For this problem, we propose a new class of subband ADFs which has two kinds of Analysis Filter banks. We first claim that subband ADFs with the optimum Analysis Filter bank, which can minimize the least squares error at each bin, can be designed in accordance with the statistics of the signals. We also propose a practical type of subband ADF which requires no a priori knowledge of the the signals statistics. Several computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filters.

  • ICASSP - A subband adaptive Filter with a variable Analysis Filter bank
    1996 IEEE International Conference on Acoustics Speech and Signal Processing Conference Proceedings, 1
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters (ADFs) using Filter banks have shown degradation in its performance because of the non-ideal nature of Analysis Filters. For this problem, we propose a new class of subband ADF which has two kinds of Analysis Filter banks. We first claim that subband ADFs with the optimum Analysis Filter bank, which can minimize the least squares error at each bin, can be designed in accordance with the statistics of the signals. We also propose a practical type of subband ADF which requires no a priori knowledge of the statistics regarding the signals. Several computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filter.

  • ICASSP - A subband adaptive Filter with the optimum Analysis Filter bank
    1995 International Conference on Acoustics Speech and Signal Processing, 1
    Co-Authors: Hiroshi Ochi, Yoshito Higa, S. Kinjo
    Abstract:

    Conventional subband ADFs (adaptive digital Filters) using Filter banks have shown degradation in performance because of the non-ideal nature of Filters. For this problem, we propose a new type of subband ADF incorporating two types of Analysis Filter bank. In this paper, we show that we can design the optimum Filter bank which minimizes the LMSE (least mean squared error). In other words, we can design a subband ADF with less MSE than that of conventional subband ADFs.

  • A subband adaptive Filter with two types of Analysis Filter bank
    Proceedings of 1994 28th Asilomar Conference on Signals Systems and Computers, 1
    Co-Authors: Hiroshi Ochi, Yoshito Higa, S. Kinjo
    Abstract:

    Conventional subband ADFs (adaptive digital Filters) using Filter banks have shown degradation in performance because of the non-ideal nature of Filters. For this problem, we propose a new type of subband ADF incorporating two types of analyses Filter bank. We show that we can design the optimum Filter bank which minimizes the LMSE (least mean squared error). In other words, we can design a subband ADF with less MSE than that of conventional subband ADFs. >

Hiroshi Ochi - One of the best experts on this subject based on the ideXlab platform.

  • A subband adaptive Filter with the statistically optimum Analysis Filter bank
    IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1998
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters using Filter banks have shown degradation in their performance because of the nonideal nature of Analysis Filters. For this problem, we propose two kinds of subband adaptive digital Filters. The first one has the statistically optimum Analysis Filter bank which minimizes error signals. This first method, however, needs some statistics of the signals; therefore, we propose another type of subband adaptive digital Filter which requires no a priori knowledge of the statistics regarding the signals. Computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filters.

  • A subband adaptive Filter with a variable Analysis Filter bank
    Conference Record of The Twenty-Ninth Asilomar Conference on Signals Systems and Computers, 1
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters (ADFs) using Filter banks have shown performance degradation because of the non-ideal nature of the Analysis Filters. For this problem, we propose a new class of subband ADFs which has two kinds of Analysis Filter banks. We first claim that subband ADFs with the optimum Analysis Filter bank, which can minimize the least squares error at each bin, can be designed in accordance with the statistics of the signals. We also propose a practical type of subband ADF which requires no a priori knowledge of the the signals statistics. Several computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filters.

  • ICASSP - A subband adaptive Filter with a variable Analysis Filter bank
    1996 IEEE International Conference on Acoustics Speech and Signal Processing Conference Proceedings, 1
    Co-Authors: Yoshito Higa, Hiroshi Ochi, S. Kinjo
    Abstract:

    Conventional subband adaptive digital Filters (ADFs) using Filter banks have shown degradation in its performance because of the non-ideal nature of Analysis Filters. For this problem, we propose a new class of subband ADF which has two kinds of Analysis Filter banks. We first claim that subband ADFs with the optimum Analysis Filter bank, which can minimize the least squares error at each bin, can be designed in accordance with the statistics of the signals. We also propose a practical type of subband ADF which requires no a priori knowledge of the statistics regarding the signals. Several computer simulations are also given in order to show the efficiency of the proposed subband adaptive digital Filter.

  • ICASSP - A subband adaptive Filter with the optimum Analysis Filter bank
    1995 International Conference on Acoustics Speech and Signal Processing, 1
    Co-Authors: Hiroshi Ochi, Yoshito Higa, S. Kinjo
    Abstract:

    Conventional subband ADFs (adaptive digital Filters) using Filter banks have shown degradation in performance because of the non-ideal nature of Filters. For this problem, we propose a new type of subband ADF incorporating two types of Analysis Filter bank. In this paper, we show that we can design the optimum Filter bank which minimizes the LMSE (least mean squared error). In other words, we can design a subband ADF with less MSE than that of conventional subband ADFs.

  • A subband adaptive Filter with two types of Analysis Filter bank
    Proceedings of 1994 28th Asilomar Conference on Signals Systems and Computers, 1
    Co-Authors: Hiroshi Ochi, Yoshito Higa, S. Kinjo
    Abstract:

    Conventional subband ADFs (adaptive digital Filters) using Filter banks have shown degradation in performance because of the non-ideal nature of Filters. For this problem, we propose a new type of subband ADF incorporating two types of analyses Filter bank. We show that we can design the optimum Filter bank which minimizes the LMSE (least mean squared error). In other words, we can design a subband ADF with less MSE than that of conventional subband ADFs. >