Discrete sine transform

About: Discrete sine transform is a research topic. Over the lifetime, 3269 publications have been published within this topic receiving 73181 citations.

Programable filter using chirp-Z transform

Abstract: A transform structure employing surface wave devices performs Fourier transform operations on a time-limited substantially band limited signal. The output signal of the transform structure is related to the Fourier transform of the input signal in a manner which permits forming the product of this output with a similar output of a second transform structure. This product is inverted by a third transform structure so as to provide the convolution of the two original input functions. The overall structure comprises a filter apparatus readily programable in either the time or frequency domain.

Computer-Aided Diagnosis System for Alzheimer's Disease Using Different Discrete Transform Techniques.

Abstract: The different discrete transform techniques such as discrete cosine transform (DCT), discrete sine transform (DST), discrete wavelet transform (DWT), and mel-scale frequency cepstral coefficients (MFCCs) are powerful feature extraction techniques. This article presents a proposed computer-aided diagnosis (CAD) system for extracting the most effective and significant features of Alzheimer’s disease (AD) using these different discrete transform techniques and MFCC techniques. Linear support vector machine has been used as a classifier in this article. Experimental results conclude that the proposed CAD system using MFCC technique for AD recognition has a great improvement for the system performance with small number of significant extracted features, as compared with the CAD system based on DCT, DST, DWT, and the hybrid combination methods of the different transform techniques.

A winograd-Fourier transform algorithm for real-valued data

Abstract: A modified version of the Winograd-Fourier transform algorithm is presented for use in transforming real vectors. The new algorithm uses real arithmetic and real storage of intermediate results throughout while retaining the economy of Winograd's basic method. The derivation of the transform is explained and some programming techniques are discussed and illustrated.

Extended performance comparison of hybrid wavelet transform for image compression with varying proportions of constituent transforms

Abstract: The rapid growth of digital imaging applications have increased the need for effective image compression techniques Image compression minimizes the size of the image without degrading the quality of the image to an unacceptable level Image compression in transform domain is one of the most popular techniques Previous work has proved that the hybrid wavelet transforms (HWT) are better than the respective constituent orthogonal transforms in image compression[1, 2] Here the extended performance comparison of HWT for image compression is presented with varying the constituent transforms and the proportions of the constituent transforms to test the effect on quality of image compression The experimentation is done on set of 20 images by varying the constituent transforms, proportion of constituent transforms and compression ratios (CR) The constituent transforms used to generated HWT are Cosine transform, Sine transform, Slant transform, Kekre transform, Walsh transform and Haar transform Here five proportions of constituent transforms alias 1:16, 1:4, 1:1, 4:1, 16:1 are considered for generation of HWT Results prove that 4:1, 1:1, 1:4 proportions of constituent transforms in HWT gives better performance as compared to 1:1 proportion of constituent transforms for different compression ratios Also for 95% compression ratio, 4:1 ratio of DCT-Haarconstituent transforms in HWT gives better results 1:1 ratio of DCT-Haarconstituent transforms give better results for compression ratios between 70% and 90% For lower compression ratios, 1:4 proportions of DCT-Haarconstituent transformsin HWT gives better performance