5.1 INTRODUCTION Any action on a signal that modifies the spectral content of the signal is called filtering. This includes the enhancement or suppression of certain features of the signal and is usually achieved by the use of linear time invariant systems. There are situations where the system may change with time in a particular manner; such systems are called adaptive filters. In this sectio...

The paper analyzes the effects of round-off noise on Multiplicative Finite Impulse Response (MFIR) filters used to approximate the behavior of pole filters. General expressions to calculate the signal to round-off noise ratio of a cascade structure of Finite Impulse Response (FIR) filters are obtained and applied on the special case of MFIR filters. The analysis is based on fixed-point implemen...

In some situations of active noise control, infinite impulse response (IIR) filters are more suitable than finite impulse response (FIR) filters owing to the poles in the transfer function. A number of algorithms have been derived for applying IIR filters in active noise control; however, most of them use the direct form IIR filter structure, which faces the difficulties of checking stability a...

Finite-length impulse response (FIR) filters occupy a central place many signal processing applications which either alter the shape, frequency or the sampling frequency of the signal. FIR filters are used because of their stability and possibility to have linear-phase but require a high filter order to achieve the same magnitude specifications as compared to infinite impulse response (IIR) fil...

In multiplierless finite impulse response (FIR) filters, the product accumulation block (PAB) could be major contributor to hardware complexity, especially for high-order filters. this paper, an optimization scheme where constant multiplication and PAB are jointly optimized at bit-level is proposed minimize complexity. joint optimization, multiple multiplications (MCM) rearranged into several M...

The computational operations of stochastic computing (SC) are governed by probability rules which is different from conventional arithmetic computations. Applications of SC to digital signal and image processing problems have been recently reported in the literature. To improve the computational performance of SC based finite impulse response (FIR) digital filters, a new stochastic inner produc...

ABSTRACT This paper present on simple method for multiplier-free finite impulse response (FIR) filter design based on the cascade of comb and linearly tapered comb filters. The stopband frequency determines the length of the comb filter. The method is used for narrowband filters where the passband frequency is not more than 0.1 of the stopband frequency. The sharpening technique is used to sati...

One of the main advantages of the linear-phase FIR filters over their IIR counterparts is the fact that there exist efficient algorithms for optimizing the arbitrary-magnitude FIR filters in the minimax sense. In case of IIR filters, the design of arbitrary-magnitude filters is usually time-consuming and the convergence to the optimum solution is not always guaranteed. The most efficient method...

In this paper, the design of a Finite Impulse Response (FIR) filter based on the residue number system (RNS) is presented. We chose to implement it in the (RNS), because the RNS offers high speed and low power dissipation. This architecture is based on the single RNS multiplier-accumulator (MAC) unit. The three moduli set 1 {2 ,2 ,2 1} n n n + − , which avoids 2 1 n + modulus, is used to design...

In recent years, the Takagi–Sugeno (T–S) fuzzy model has been commonly used for the approximation of nonlinear systems. Using the T-S fuzzy model, nonlinear systems can be converted into linear time-varying systems, which can reduce approximation errors compared with the conventional Taylor approximation. In this paper, we propose a new nonlinear filter with a finite impulse response (FIR) stru...