R. Praveena ¹, S. Nirmala ²

Affiliations
1 Department of Electronics and Communication Engineering, Sengunthar College of Engineering, Tiruchengode - 637 205, Namakkal, Tamil Nadu, IN
2 Department of Electronics and Communication Engineering, Muthayammal Engineering College, Rasipuram - 637408, Namakkal, Tamil Nadu, IN

Abstract

This paper introduces a framework for the implementation of high throughput Multiplier for low Power Biomedical Signal Processing System-on-Chip (SoC) design for Portable ECG Monitoring Systems. In this paper the realization of Efficient Multiplier for the proposed architecture in the implementation of the Biomedical Signal SoC monitoring system is presented. Since the multiplier is the part of the processor core which needs more attention and a modified approach of generating partial product for successful multiplication of the bit streams has been presented. The proposed SoC incorporates a new architecture using the booth multiplier and sign extension multiplier for 4 bit, 8 bit and 16 bit performing multiplication on both signed and unsigned number. The implementation is further extended on the radix application of booth multiplier and sign extension method. Different parameters have been compared for both signed and unsigned multiplier. The implementation is done through VHDL on Quartus II synthesizer for Cyclone II family.

Keywords

Bit Serial Multiplier, MAC Unit, Radix Algorithm and Booth Recoding, Sign Extension, System on Chip.

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R. Praveena ¹, V. Sowmya ¹, K. P. Soman ¹

Affiliations
1 Centre for Computational Engineering and Networking (CEN), Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Amrita University, Coimbatore - 641112, Tamil Nadu, IN

Abstract

Noise, the unwanted information in a signal reduces the quality of signal. Hence to improve the signal quality, denoising is done. The main aim of the proposed method in this paper is to deconvolve and denoise a noisy signal by least square approach using wavelet filters. In this paper, least square approach given by Selesnick is modified by using different wavelet filters in place of second order sparse matrix applied for deconvolution and smoothing. The wavelet filters used in the proposed approach for denoising are Haar, Daubechies, Symlet, Coiflet, Biorthogonal and Reverse biorthogonal. The result of the proposed experiment is validated in terms of Peak Signal to Noise Ratio (PSNR). Analysis of the experiment results notify that proposed denoising based on least square using wavelet filters are comparable to the performances given by deconvolution and smoothing using the existing second order filter.

Keywords

Least Square, Peak Signal to Noise Ratio (PSNR), Signal Denoising, Wavelet Filters

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