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Soft Computing Techniques for the Optimization of SAW Filters: A State-of-the-art Review
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 9 - Number 4 |
| Year of Publication: 2015 |
| Authors: Prachi Chaudhary, Priyanka, Manoj Duhan |
10.5120/ijais15-451399
|
Prachi Chaudhary, Priyanka, Manoj Duhan . Soft Computing Techniques for the Optimization of SAW Filters: A State-of-the-art Review. International Journal of Applied Information Systems. 9, 4 ( July 2015), 73-80. DOI=10.5120/ijais15-451399
Abstract
Surface Acoustic Wave (SAW) devices are an important class of piezoelectric devices, providing frequency control, frequency selection, and signal processing capabilities. The SAW devices, designed to handle complex signal processing functions, can offer considerable cost & size advantage over competing technology. The SAW devices, based on the transduction of acoustic waves, are used as filters, oscillators and transformers, devices. The SAW filters are electromechanical devices commonly used in radio frequency applications. The SAW filters are of 4 types; Linear Resonator and Resonator-Filter Devices, Linear Devices Using Unidirectional IDTs, Linear Devices Using Bidirectional IDTs and Nonlinear Devices. Most of work associated with SAW filters deals with the realization of FIR filters may be quite high, resulting in a large size filter. The realization of IIR filters on SAW devices lead to substantial reduction in filter size. But the introduction of reflective units (for realizing poles lead to complex optimizations issues. Soft Computing Techniques (SCT) are the optimization techniques inspired by the cognitive behavior of human mind. These are fusion of methodologies that were designed to model and enable solutions to real world problems, which are not modeled or too difficult to model, mathematically. SCTs are classified in to four important categories; Evolutionary Computation Techniques (ECT), Fuzzy Logic (FL), Neutral Network (NN) and Machine Learning (ML) [23]. The ECTs are probability-based approaches inspired by biological evolution and/or social evolution. The ECTs are based on mechanics of natural selection and natural genetics, of the likes Genetic algorithms (GAs) and local search have already been used in various forms for solving optimization issues related to SAW filter design. Newer ECTs like Memetic Algirithms (MAs), which blends GAs and local search to take care of both the exploration and exploitation of search space, have also been reported to be used for the optimization of some of the SAW filter design. The main goal of the report in this paper is to look in to the use of SCTs for tackling SAW filter design issues and in that context, probe the future scenario of these techniques for such design issues.
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