A NOVEL ANALYTICAL METHOD FOR THE SELECTIVE MULTIPLIERLESS LINEAR-PHASE 2D FIR FILTER FUNCTION

In this paper, a novel analytical method for new class of selective linear-phase two-dimensional (2D) finite impulse response (FIR) filter functions generated by applying a new modified 2D Christoffel–Darboux formula for classical orthogonal Chebyshev polynomials of the first and the second kind is proposed. Fundamental research proposed in this paper is also illustrated by examples of 2D FIR filter and adequate comparison with new class of multiplierless linear-phase 2D FIR filter function given in the literature

Efficient Implementation of Multiplierless Recursive Lowpass FIR Filters using Computer Algebra System

Abstract: The efficient implementation of a selective multiplierless lowpass digital FIR filter is a desired solution for low-power consumption applications. The simplest way is to start the design procedure that is based on predefined efficient filter structure. The computer algebra system can be used for the automated design procedure. The proposed solution is especially attractive in cases when the same hardware can be used more than ones during the sampling period. Also, the overall complexity is equivalent to very low-order FIR filter, while the filter order that corresponds to the filter transfer function is very high

Efficient recursive implementation of multiplierless FIR filters

Abstract: The efficient implementation of selective multiplierless digital FIR filter is very desired solution for low-power consumption applications. Filter requirements such as sharp transition and large stop-band attenuation require very high filter order and usually large power consumption. The solution of this problem can be to use predefined hardware filter structures with small number of operations per input sample in spite of the very high filter order. In this paper we provide a systematic approach for solving the problem using computer algebra system (CAS). The methodology is based on (1) sketching the filter structure that is known to have excellent properties appropriate as embedded solution, (2) automated building the knowledge into CAS in a form of the schematic description, (3) automated derivation of filter properties such as transfer functions or implementation codes, (4) defining a strategy for combining intermediate results, and (5) plotting the frequency responses in order to verify the final solution