NDLI: Design and implementation of fft processor using vedic multiplier with high throughput.

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Design and implementation of fft processor using vedic multiplier with high throughput.

Content Provider	CiteSeerX
Author	Agarwal, Jyoti Matta, Vijay Arya, Dwejendra
Abstract	Abstract- In present scenario every process should be rapid, efficient and simple. Fast Fourier transform (FFT) is an efficient algorithm to compute the N point DFT. It has great applications in communication, signal and image processing and instrumentation. But the Implementation of FFT requires large number of complex multiplications, so to make this process rapid and simple it’s necessary for a multiplier to be fast and power efficient. To tackle this problem Urthva Tirvagbhyam in Vedic mathematics is an efficient method of multiplication [4]. Vedic Mathematics is the ancient system of mathematics which has a unique technique of calculations based on 16 Sutras. Employing these techniques in the computation algorithms of the coprocessor will reduce the complexity, execution time, area, power etc. Urdhva Tiryakbhyam one of the sutra of Vedic Mathematics, being a general multiplication formula, is equally applicable to all cases of multiplication. The conventional multiplication method requires more time & area on silicon than Vedic algorithms [8]. More importantly processing speed increases with the bit length. This will help ultimately to speed up the signal processing task. The novelty in this paper is Fast Fourier Transform (FFT) design methodology using Vedic mathematics algorithm. By combining these two approaches proposed design methodology is time-area-power efficient.
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Access Restriction	Open
Subject Keyword	Vedic Mathematics High Throughput Fft Processor Using Vedic Multiplier Fast Fourier Transform Design Methodology Signal Processing Task General Multiplication Formula Point Dft Large Number Power Efficient Image Processing Power Etc Unique Technique Speed Increase Efficient Algorithm Ancient System Time-area-power Efficient Efficient Method Bit Length Great Application Problem Urthva Tirvagbhyam Time Area Execution Time Computation Algorithm Complex Multiplication Urdhva Tiryakbhyam Present Scenario Conventional Multiplication Method Vedic Mathematics Algorithm
Content Type	Text
Resource Type	Article

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