Introduction
The DSP world today is ruled by different transforms. Discrete Fourier transforms are most used. So is the fast Fourier transform, which is the faster version of DFT. Suppose we take FFT of a signal. On taking the inverse fast Fourier transform, we except the output to be the same as the input. This is called the invertibility property. But on most occasions, disappointment is the result. This is due to the finite word length of the registers used to store the samples and the coefficients. This seminar introduces a method called i ....etc

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A 64 Point Fourier Transform Chip

Fourth generation wireless and mobile system are currently the focus of research and development. Broadband wireless system based on orthogonal frequency division multiplexing will allow packet based high data rate communication suitable for video transmission and mobile internet application. Considering this fact we proposed a data path architecture using dedicated hardwire for the baseband processor. The most computationally intensive part of such a high data rate system are the 64-point inverse FFT in the ....etc

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For many years signal analyses and processing are being done either in frequency domain or in time domain. However, information about both time and frequency is needed in many cases for proper signal analysis. Multi resolution analysis is a relatively new concept that tries to get time as well as frequency information simultaneously. Wavelet transform is perhaps the most popular technique of multiresolution analysis. The seminar introduces basic concepts of wavelets and multiresolution analysis with respect to its application ....etc

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Abstract
I have implemented the Fast Fourier Transform (FFT) algorithm, using the method of Cooley-Tukey. The FFT reduces the computation required in determining the Fourier Transform, which is used in several applications in science and engineering, including signal processing computations and spectral analysis. The Cooley-Tukey method primarily uses binary logic, making use of the symmetry and periodicity properties of complex exponentials. Substantial savings can be made in computation, especially when the number of input sample values is ....etc

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image compression using ridgelet transform matlab codes ....etc

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A PIPELINE FAST FOURIER TRANSFORM FOR DIGITAL SPECTRUM ANALYSIS

Abstract:- This paper describes a novel structure for a hardwired fast Fourier transform (FFT) signal processor that promises to permit digital spectrum analysis to achieve throughput rates consistent with extremely wide-band radars. The technique is based on the use of serial storage for data and intermediate results and multiple arithmetic units each of which carries out a sparse Fourier transform. Details of the system are described for data sample sizes that are binary multi ....etc

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Abstract
In this paper, we propose an implementation of the 3-D ridgelet transform: The 3-D Discrete Analytical Ridgelet Transform
(3-D DART). This transform uses the Fourier strategy for the computation of the associated 3-D discrete Radon transform. The
innovative step is the definition of a discrete 3-D transform with the discrete analytical geometry theory by the construction of
3-D discrete analytical lines in the Fourier domain. We propose two types of 3-D discrete lines: 3-D discrete radial lines going
through the origin def ....etc

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PREFACE

The DSP world today is ruled by different transforms. Discrete Fourier transforms are most used. So is the fast Fourier transform, which is the faster version of DFT.
Suppose we take FFT of a signal. On taking the inverse fast Fourier transform,we except the output to be the same as the input.This is called the invertibility property.But on most occasions, dissapointment is the result. This is due to the finite word length of the registers used to store the samples and the coefficients.
This seminar introduces a method called integ ....etc

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....etc

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