Discrete-time signal processing
Discrete-time signal processing
Low-Area/Power Parallel FIR Digital Filter Implementations
Journal of VLSI Signal Processing Systems
Implementing a RAKE receiver for wireless communications on an FPGA-based computer system
FPGA '00 Proceedings of the 2000 ACM/SIGDA eighth international symposium on Field programmable gate arrays
Application of Reconfigurable Computing to a High Performance Front-End Radar Signal Processor
Journal of VLSI Signal Processing Systems
Analysis and FPGA Implementation of Image Restoration under Resource Constraints
IEEE Transactions on Computers
FCCM '00 Proceedings of the 2000 IEEE Symposium on Field-Programmable Custom Computing Machines
Constant Coefficient Multiplication Using Look-Up Tables
Journal of VLSI Signal Processing Systems
Journal of VLSI Signal Processing Systems
Reconfigurable Computing: The Theory and Practice of FPGA-Based Computation
Reconfigurable Computing: The Theory and Practice of FPGA-Based Computation
1-D fast normalized cross-correlation using additions
Digital Signal Processing
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As Field Programmable Gate Array (FPGA) technology has steadily improved, FPGAs are now viable alternatives to other technology implementations for high-speed classes of digital signal processing (DSP) applications. In particular, radar front-end signal processing, an application formerly dominated by custom very large scale integration (VLSI) chips, may now be a prime candidate for migration to FPGA technology. As this paper demonstrates, current FPGA devices have the power and capacity to implement a FIR filter with the performance and specifications of an existing, in-system, front-end signal processing custom VLSI chip. A 512-tap, 18-bit FIR filter was built that could achieve sample rates of 5 MHz (with a clock rate of at least 40 MHz) using Xilinx Virtex FPGA technology, and was demonstrated through simulation. Distributed arithmetic was determined to be the most optimal structure for a FPGA FIR design, although future research may show that fast FIR algorithms or filtering in the frequency domain might give better results.