This paper proposes a solution methodology for the design of optimal and stable digital infinite impulse response (IIR) band stop (BS) filter by employing modified cat swarm optimization (CSO) algorithm. The error surface of digital IIR filters is non linear and multimodal because of the presence of the denominator terms. Therefore, the traditional filter design methods usually got stuck in the...

A solution methodology for the design of digital infinite impulse response (IIR) filter considering multiple conflicting objectives has been proposed. The nucleus of the method is that multiple objectives can be attuned suitably, to optimize the performance in pass bands, stop bands and transition bands of IIR digital filters. The proposed method uses multiobjective optimization approach for de...

Digital filtering is an integral part of many digital signal processing algorithms. Digital filters are characterized as either recursive [infinite impulse response (IIR)] or non-recursive [finite impulse response (FIR)] filters. IIR filters require a smaller order for the same set of specifications compared to FIR filters, while FIR filters provide a linear phase property. However, IIR filters...

a fundamental aspect of signal processing is filtering. Filtering involves the manipulation of the spectrum of a signal by passing or blocking certain portions of the spectrum, depending on the frequency of those portions. In this paper, Digital filters are designed using frequency specifications. Matlab provides different options for digital filter design, which includes function, calls to fil...

a fundamental aspect of signal processing is filtering. Filtering involves the manipulation of the spectrum of a signal by passing or blocking certain portions of the spectrum, depending on the frequency of those portions. In this paper, Digital filters are designed using frequency specifications. Matlab provides different options for digital filter design, which includes function, calls to fil...

The common conviction about FIR (finite impulse response) digital filters is that the number of necessary taps, to reach the same performance as provided by IIR (infinite impulse response) digital filters, is usually too large. Moreover, the standard FIR filter design algorithm (Remez exchange) allows the design of linear-phase filters only. Therefore, IIR filters are often preferred over FIR o...

This paper presents an evolutionary design of digital IIR filters using the genetic algorithm (GA) with modified genetic operators and real-valued encoding. Conventional digital IIR filter design methods involve algebraic transformations of the transfer function of an analog low-pass filter (LPF) that satisfies prescribed filter specifications. Other types of frequency-selective digital filters...

In software radio systems, a digital IIR filter offers good roll-off and transition bandwidth characteristics using a low amount of arithmetic components, thus simplifying hardware implementation. However, IIR filter structures are very sensitive to finite precision compared to FIR filter structures. In order to design a high quality, low component count, digital narrowband bandpass filter onto...

Adaptive infinite-impulse-response (IIR) filtering provides a powerful approach for solving a variety of practical problems. Because the error surface of IIR filters is generally multi-modal, global optimisation techniques are required in order to avoid local minima. We apply a global optimisation method, called the adaptive simulated annealing (ASA), to digital IIR filter design. An important ...

The paper presents a greedy search method based on binary successive approximation-evolutionary search (BSA-ES) strategy to design stable infinite impulse response (IIR) digital filter using L1 optimality criterion. The stability constraints are well taken care of during the design procedure. The filter designed based on L1-approximation error possesses flat pass-bands and stop-bands to that of...