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Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

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Published on: February 4, 2018

Optimal multiobjective design of digital filters using spiral optimization technique.

Abderrahmane Ouadi¹, Hamid Bentarzi, Abdelmadjid Recioui

¹Laboratory signals and systems, Institute of Electrical and Electronic Engineering, University M'hamed Bougara Boumerdes, Avenue de l'indépendance, Boumerdes, 35000 Algeria.

|October 2, 2013

Summary

This study introduces a novel spiral optimization technique for designing digital filters. The method effectively matches desired frequency responses and minimizes linear phase, yielding practical filter designs.

Keywords:

Group delay Magnitude response Minimum linear phase Multiobjective filter design Spiral optimization technique

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Area of Science:

Digital Signal Processing
Optimization Techniques

Background:

Digital filter design is crucial for signal processing applications.
Traditional methods can struggle with multiobjective optimization and local optima.

Purpose of the Study:

To introduce and evaluate a novel spiral optimization technique for multiobjective digital filter design.
To demonstrate the technique's ability to match desired frequency responses and minimize linear phase.

Main Methods:

A metaheuristic optimization technique inspired by spiral dynamics was employed.
The technique was applied to the multiobjective design of digital filters.

Main Results:

The spiral optimization technique proved robust and resistant to local optima.
The designed filters met desired frequency response and linear phase characteristics.
The method demonstrated relative fast convergence and ease of implementation.

Conclusions:

The spiral optimization technique is a viable and effective tool for digital filter design.
The proposed approach yields practical filters with desired performance characteristics.