Custom coprocessor based matrix algorithms for image and signal processing

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Abstract

Matrix algorithms are important in many types of applications including image and signal processing. A close examination of the algorithms used in these, and related, applications reveals that many of the fundamental actions involve matrix algorithms such as matrix multiplication. This paper presents an investigation into the design and implementation of different matrix algorithms such as matrix operations, matrix transforms and matrix decompositions using a novel custom coprocessor system for MATrix algorithms based on Reconfigurable Computing (RCMAT). The proposed RCMAT architectures are scalable, modular and require less area and time complexity with reduced latency when compared with existing structures. © Springer-Verlag Berlin Heidelberg 2002.

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APA

Amira, A., Bouridane, A., Milligan, P., & Bensaali, F. (2002). Custom coprocessor based matrix algorithms for image and signal processing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2438 LNCS, pp. 730–739). Springer Verlag. https://doi.org/10.1007/3-540-46117-5_75

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