Coefficient quantization effects on new filters based on Chebyshev fourth-kind polynomials

The aim of this paper is to construct non-recursive filters, extensively used type of digital filters in digital signal processing applications, based on Chebyshev orthogonal polynomials. The paper proposes the use of the fourth-kind Chebyshev polynomials as functions in generating new filters. In this kind, low-pass filters with linear phase responses are obtained. Comprenhansive study of the frequency response characteristics of the generated filter functions is presented. The effects of coefficient quantization as one type of quantization that influences a filter characteristic are investigated here also. The quantized-coefficient errors are considered based on the number of bits and the implementation algorithms.

A Novel Multilayer Structure with Frequency Selected Surface for Electromagnetic Compatibility

Electromagnetic wave absorbers can be widely used in Electromagnetic Compatibility (EMC). We proposed a novel multilayer structure of metal alloy-ferrite-plastic composites. A new structure with Frequency Selected Surface (FSS), which has filter characteristic, embedded in the composites was fabricated to improve the absorption performance. In bandwidth of 8.04GHz, the reflectivity was smaller than-8dB and the thickness was only 2.6mm. The reflectivity was measured using a standard NRL Arch technique in a frequency range of 3-18 GHz. The experimental results indicate that it is possible to make a desirable thin, broadband EMW absorber by the incorporation of an FSS into the magnetic absorbing materials.

A novel variable filter band discrete wavelet transform: Theory and principle

It is well-known that a mother wavelet for the discrete wavelet transform (DWT) has the band-pass filter characteristic with octave width in the frequency domain and can be used for octave analysis. However, it is possible that the octave analysis is not necessarily the most suitable to match the analysis signal. In this study, in order to construct the most suitable basis to match the analysis signal, a novel variable-filter band discrete wavelet transform (VFB-DWT) is proposed. It is achieved by using variable-band filters instead of conventional decomposition and reconstruction sequences, which are designed in consideration of the real signal characteristics. Additionally, it is proven that perfect reconstruction of the analysis signal by VFB-DWT is guaranteed using the perfect shift invariant theorem that underlies the theory of the PTI-CDWT having base DWT.