Type of Document Dissertation Author Guo, Rui Author's Email Address email@example.com URN etd-07062011-165129 Title Efficient Hardware Implementation Techniques For Digital Filters Degree Doctor of Philosophy Department Electrical and Computer Engineering, Department of Advisory Committee
Advisor Name Title Linda DeBrunner Committee Chair Bruce Harvey Committee Member Rodney Roberts Committee Member Victor DeBrunner Committee Member Gary Tyson University Representative Keywords
- Distributed Arithmetic
- Digital Filter
Date of Defense 2011-06-29 Availability unrestricted AbstractThis dissertation addresses the development of efficient digital filter implementation techniques. Measures for area, latency, and throughput are used to quantify the benefits of the proposed implementation schemes, as well as consideration of the digital signal processing algorithm performance.
Multiple-constant multiplication (MCM) is a popular approach for implemented fixed coefficient finite impulse response (FIR) filters. We propose two methods for truncating addition results in an MCM implementation that reduce the area required while decreasing latency. The effects of filter order and coefficient quantization are explored by the proposed search technique that reduces the computations required by an MCM implementation.
Two new adaptive filter implementation techniques based on distributed arithmetic (DA) are proposed that provide reduced area and speed without loss of filter performance. Adaptive filter implementations can also be based on real-time conversion of the adapted coefficients into a canonical-signed-digit (CSD) representation. We propose a new conversion circuit that reduces both latency and area. Fine-grained parallelism and relaxed look-ahead techniques are applied to develop a pipelined Gauss-Seidel fast affine projection (GSFAP) adaptive filter implementation that allow degradation to the adaptive filter performance and increases area to achieve significantly faster performance.
These proposed techniques for fixed coefficient and adaptive filters can be used for applications in which low area and high speed implementations are required.
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