Synopsis
Discrete Fourier Transform (DFT) and Finite Impulse Response (FIR) filters are extensively used in Digital Signal Processing (DSP) and Image Processing. In this book, an arithmetic Sum-of-Product (SOP) based approach to implement area- and delay-efficient DFT and FIR filter circuits is presented. The proposed SOP based engine uses an improved column compression algorithm, and handles the sign of the input efficiently. The partial products of the computation are compressed down to two operands, which are then added using a single hybrid adder. The problem of synthesizing DFT and FIR filters circuits can also be cast as an instance of the Multiple Constant Multiplication (MCM) problem. RAG-n is one of the best known algorithms for realizing an MCM block with the minimum number of adders. For DFT coefficients, the proposed approach yields faster circuits (by about 12-13%) with low area penalty (about 5%), as compared to RAG-n. Significant speed-ups are also observed for a set of FIR filters with hard-to-implement coefficients.
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About the Author
Rajeev Kumar received his B. Tech. degree in Electronics and Communication Engg. from Indian Institute of Technology Guwahati, India in May 2007, and his Masters Degree in Computer Engg. from Texas A&M University in May 2013. From 2007 to 2010, he worked as Design Engineer at ARM, India. His research interests are in VLSI CAD and circuit design.
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A Sum-Of-Product Based Multiplication Approach For FIR Filters And DFT
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Discrete Fourier Transform (DFT) and Finite Impulse Response (FIR) filters are extensively used in Digital Signal Processing (DSP) and Image Processing. In this book, an arithmetic Sum-of-Product (SOP) based approach to implement area- and delay-efficient DFT and FIR filter circuits is presented. The proposed SOP based engine uses an improved column compression algorithm, and handles the sign of the input efficiently. The partial products of the computation are compressed down to two operands, which are then added using a single hybrid adder. The problem of synthesizing DFT and FIR filters circuits can also be cast as an instance of the Multiple Constant Multiplication (MCM) problem. RAG-n is one of the best known algorithms for realizing an MCM block with the minimum number of adders. For DFT coefficients, the proposed approach yields faster circuits (by about 12-13%) with low area penalty (about 5%), as compared to RAG-n. Significant speed-ups are also observed for a set of FIR filters with hard-to-implement coefficients. 64 pp. Englisch. Seller Inventory # 9783848486366
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A Sum-Of-Product Based Multiplication Approach For FIR Filters And DFT
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar RajeevRajeev Kumar received his B. Tech. degree in Electronics and Communication Engg. from Indian Institute of Technology Guwahati, India in May 2007, and his Masters Degree in Computer Engg. from Texas A&M University in May 2. Seller Inventory # 5526310
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A Sum-Of-Product Based Multiplication Approach For FIR Filters And DFT
Published by
LAP LAMBERT Academic Publishing Jan 2014, 2014
ISBN 10: 3848486369
ISBN 13: 9783848486366
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Discrete Fourier Transform (DFT) and Finite Impulse Response (FIR) filters are extensively used in Digital Signal Processing (DSP) and Image Processing. In this book, an arithmetic Sum-of-Product (SOP) based approach to implement area- and delay-efficient DFT and FIR filter circuits is presented. The proposed SOP based engine uses an improved column compression algorithm, and handles the sign of the input efficiently. The partial products of the computation are compressed down to two operands, which are then added using a single hybrid adder. The problem of synthesizing DFT and FIR filters circuits can also be cast as an instance of the Multiple Constant Multiplication (MCM) problem. RAG-n is one of the best known algorithms for realizing an MCM block with the minimum number of adders. For DFT coefficients, the proposed approach yields faster circuits (by about 12-13%) with low area penalty (about 5%), as compared to RAG-n. Significant speed-ups are also observed for a set of FIR filters with hard-to-implement coefficients.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Seller Inventory # 9783848486366
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A Sum-Of-Product Based Multiplication Approach For FIR Filters And DFT
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LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3848486369
ISBN 13: 9783848486366
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Discrete Fourier Transform (DFT) and Finite Impulse Response (FIR) filters are extensively used in Digital Signal Processing (DSP) and Image Processing. In this book, an arithmetic Sum-of-Product (SOP) based approach to implement area- and delay-efficient DFT and FIR filter circuits is presented. The proposed SOP based engine uses an improved column compression algorithm, and handles the sign of the input efficiently. The partial products of the computation are compressed down to two operands, which are then added using a single hybrid adder. The problem of synthesizing DFT and FIR filters circuits can also be cast as an instance of the Multiple Constant Multiplication (MCM) problem. RAG-n is one of the best known algorithms for realizing an MCM block with the minimum number of adders. For DFT coefficients, the proposed approach yields faster circuits (by about 12-13%) with low area penalty (about 5%), as compared to RAG-n. Significant speed-ups are also observed for a set of FIR filters with hard-to-implement coefficients. Seller Inventory # 9783848486366
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A Sum-Of-Product Based Multiplication Approach For FIR Filters And DFT
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Taschenbuch. Condition: Neu. A Sum-Of-Product Based Multiplication Approach For FIR Filters And DFT | Rajeev Kumar (u. a.) | Taschenbuch | 64 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783848486366 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 105497572
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