Pipelined systolic architectures for DLMS adaptive filtering

Thomas, J.

doi:10.1007/bf00924987

Cited by 16 publications

(7 citation statements)

References 16 publications

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“…(19) for DLMS in each configuration. In Douglass configuration, L(n) is calculated recursively and hence the effect of finite word length appears in realization.…”

Section: Architecturementioning

confidence: 99%

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Pipeline implementation of gradient-type adaptive filters

Nishikawa

Kiya

2001

Electron. Comm. Jpn. Pt. III

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“…(19) for DLMS in each configuration. In Douglass configuration, L(n) is calculated recursively and hence the effect of finite word length appears in realization.…”

Section: Architecturementioning

confidence: 99%

“…In configuration (i), the length of CP is 2W m + 2W a that is longer than the one given by Eq. (19) for CP of DLMS. In configuration (ii), the length of CP is equal to Eq.…”

Section: Pipeline Configuration Based On Lmsmentioning

confidence: 99%

Pipeline implementation of gradient-type adaptive filters

Nishikawa

Kiya

2001

Electron. Comm. Jpn. Pt. III

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“…1,2 In many adaptive filtering applications, very high sample rates, and/or filters of large size, are required. [3][4][5][6][7][8][9] The computational burden of the adaptation mechanism becomes extremely high, and processing power of several GOPS (Giga operations per second) is needed. This means that for a real-time implementation, pipelined and/or parallel computational architectures should be developed.…”

Section: Introductionmentioning

confidence: 99%

“…A remedy to this bottleneck is the engagement of Delayed LMS (D-LMS) schemes. [5][6][7][8][9][10]12,13 The D-LMS algorithm, originally proposed in Ref. 12, gave rise to the development of high throughput pipelineable and/or parallel schemes for the implementation of the LMS filter, on ASIC VLSI systolic, or on wavefront array processors.…”

Section: Introductionmentioning

confidence: 99%

Pipelined Architectures for Transform Domain LMS Adaptive Filtering

Glentis

2005

J CIRCUIT SYST COMP

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In this paper, efficient pipelined architectures for the implementation of the Transform Domain LMS (TD-LMS) adaptive filter are considered. Pipelining of the TD-LMS algorithm is achieved by introducing an amount of time delay into the original adaptive scheme. The resulting algorithm, called thereafter the delayed TD-LMS, performs adaptive filtering with delayed coefficients adaptation. A statistical performance analysis of the proposed delayed TD-LMS adaptive algorithm is presented, both for the mean error and the mean squared error of the filter coefficients. A closed form expression is derived for the estimation of the steady state excess mean squared error, in terms of the adaptation delay and the input signal characteristics. The adaptation delay introduced to the delayed TD-LMS algorithm is subsequently utilized for the development of pipelined architectures. By retiming the delays existing in the error signal feedback loop, efficient pipelined implementations of the delayed TD-LMS algorithm are developed. The proposed architectures are suitable for parallel implementation on a general-purpose parallel machine, or on dedicated hardware, integrated on ASIC or ASIP VLSI processors.

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“…Many architectures for the pipelined implementation of the least mean square (LMS) ADFs have been proposed [3,4,5,6,7,8,9,101 and using these architectures, LMS ADFs can be operated at desired throughput levels. The rates of convergence of them however are smaller than those of RLS ADFs, whose throughput rate is lower because of their computational requirements.…”

Section: Introductionmentioning

confidence: 99%

Fast implementation technique for improving throughput of RLS adaptive filters

Nishikawa

Kiya²

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)

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This paper proposes a fast implementation technique for RLS adaptive filters. The technique has an adjustable parameter to trade the throughput and the rate of convergence of the filter according to the applications. The conventional methods for improving the throughput do not have this kind of adjustability so that the proposed technique will expand the area of applications for the RLS algorithm. We show that the improvement of the throughput can be easily achieved by rearranging the formula of the RLS algorithm and that there are no need for faster PES for the improvement.

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Pipelined systolic architectures for DLMS adaptive filtering

Cited by 16 publications

References 16 publications

Pipeline implementation of gradient-type adaptive filters

Pipeline implementation of gradient-type adaptive filters

Pipelined Architectures for Transform Domain LMS Adaptive Filtering

Fast implementation technique for improving throughput of RLS adaptive filters

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