FPGA Based Adaptive Filter Design Using Least PTH-Norm Technique
Srishtee Chaudhary1, Rajesh Mehra2
1Srishtee Chaudhary, Electronics and Comm. Eng. Dept., Govt. Polytechnic College for Girls, Patiala, India.
2Rajesh Mehra, Associate Professor, Electronics and Comm. Eng. Dept., NITTTR, Chandigarh, India.
Manuscript received on April 08, 2013. | Revised Manuscript received on April 29, 2013. | Manuscript published on May 05, 2013. | PP: 208-212 | Volume-3, Issue-2, May 2013. | Retrieval Number: B1500053213/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Adaptive filters are considered nonlinear systems; therefore their behavior analysis is more complicated than for fixed filters. As adaptive filters are self-designing filters, their design can be considered less involved than in the case of digital filters with fixed coefficients. This paper presents simulation of Low Pass FIR Adaptive filter using least mean square (LMS) algorithm and least Pth norm algorithm. LMS algorithm is a type of adaptive filter known as stochastic gradient-based algorithms as it utilizes the gradient vector of the filter tap weights to converge on the optimal wiener solution whereas Least Pth does not need to adapt the weighting function involved and no constraints are imposed during the course of optimization. In this paper FPGA implementation of a low pass FIR filter is done using least Pth-norm technique. The performance of both approaches is compared.
Keywords: Adaptive filters, FIR , Least Pth norm, LMS, Matlab, FPGA.