Architectural Synthesis of Low-Power Computational Engines for LMS Adaptive Filtering
نویسندگان
چکیده
The stochastic-gradient-descent LMS adaptive filtering algorithm provides a powerful and computationally efficient means of realizing adaptive filters. In this work, we present architectural synthesis of low-power computational engines (or hardware accelerators) for LMS adaptive filtering. This engine could be configured for delayed LMS/delayed normalized LMS, full-band/subband adaptive filtering depending on the application requirements.
منابع مشابه
Architectural Synthesis of Computational Engines for Subband Adaptive Filtering
Architectural synthesis of low-power computational engines (hardware accelerators) for a subband-based adaptive ltering algorithm is presented. The full-band least mean square (LMS) adaptive ltering algorithm, widely used in various applications, is confronted by two problems, viz., slow convergence when the input correlation matrix is ill-conditioned, and increased computational complexity for...
متن کاملSpeech Enhancement by Modified Convex Combination of Fractional Adaptive Filtering
This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS) is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS ...
متن کاملImage Restoration with Two-Dimensional Adaptive Filter Algorithms
Two-dimensional (TD) adaptive filtering is a technique that can be applied to many image, and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to TD structures and the novel TD adaptive filters are established. Based on this extension, the TD variable step-size normalized least mean squares (TD-VSS-NLMS), the TD-VSS affine projection algorithms (...
متن کاملOptimized computational Afin image algorithm using combination of update coefficients and wavelet packet conversion
Updating Optimal Coefficients and Selected Observations Affine Projection is an effective way to reduce the computational and power consumption of this algorithm in the application of adaptive filters. On the other hand, the calculation of this algorithm can be reduced by using subbands and applying the concept of filtering the Set-Membership in each subband. Considering these concepts, the fir...
متن کاملA Family of Selective Partial Update Affine Projection Adaptive Filtering Algorithms
In this paper we present a general formalism for the establishment of the family of selective partial update affine projection algorithms (SPU-APA). The SPU-APA, the SPU regularized APA (SPU-R-APA), the SPU partial rank algorithm (SPU-PRA), the SPU binormalized data reusing least mean squares (SPU-BNDR-LMS), and the SPU normalized LMS with orthogonal correction factors (SPU-NLMS-OCF) algorithms...
متن کامل