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Filtering data in real-time requires dedicated hardware to meet demanding time requirements. If the statistics of the signal are not known, then adaptive filtering algorithms can be implemented to estimate the signals statistics iteratively. Modern field programmable gate arrays (FPGAs) include the resources needed to design efficient filtering structures. Furthermore, some manufacturers now include complete microprocessors within the FPGA fabric. This mix of hardware and embedded software on a single chip is ideal for fast filter structures with arithmetic intensive adaptive algorithms. This thesis aims to combine efficient filter structures with optimized code to create a System-on-chip (SoC) solution for various adaptive filtering problems. Several different adaptive algorithms have been coded in VHDL as well as in C for the PowerPC 405 microprocessor. The designs are evaluated in terms of design time, filter throughput, hardware resources, and power consumption.
A Thesis Submitted to the Department of Electrical and Computer Engineering in Partial Fulfillment of the Requirements for the Degree of Master of Science.
Includes bibliographical references.
Florida State University
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