This computes an in-place complex-to-complex FFT x and y are the real and imaginary arrays of 2^m points. dir = 1 gives forward transform dir = -1 gives reverse transform
標(biāo)簽： complex-to-complex and imaginary computes
上傳時(shí)間： 2013-12-18
上傳用戶：huql11633
The tca package is a Matlab program that implements the tree-dependent component analysis (TCA) algorithms that extends the independent component analysis (ICA), where instead of looking for a linear transform that makes the data components independent, we are looking for components that can be best fitted in a tree structured graphical model. The TCA model can be applied in any situation where the data can be assumed to have been transformed by an unknown linear transformation.
標(biāo)簽： tree-dependent implements component analysis
上傳時(shí)間： 2016-09-17
上傳用戶：cazjing
1D FDTD simulation between free space and dielectric medium with absorbing boundary conditions,calculating the fourier transform of electric field
標(biāo)簽： simulation dielectric conditions absorbing
上傳時(shí)間： 2016-09-24
上傳用戶：gundamwzc
分?jǐn)?shù)階統(tǒng)一混沌系統(tǒng)的離散算法-This the program for fractional order Unified system, a simple but fast method in time domain.
標(biāo)簽： fractional program Unified method
上傳時(shí)間： 2014-01-22
上傳用戶：lo25643
These three articles involves the combination of wavelet and MCTF. MCTF means motion-compensated-time-filter. It makes wavelet transform more popular because of the high compression efficiency.
標(biāo)簽： motion-compensated-tim MCTF combination articles
上傳時(shí)間： 2013-11-25
上傳用戶：cc1015285075
Recent advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the domain of ecologists are now being used more widely. This book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique’s potential.
標(biāo)簽： experimental generation advances enormous
上傳時(shí)間： 2016-10-23
上傳用戶：wkchong
經(jīng)典分?jǐn)?shù)階傅立葉變換，土耳其算法（The fast Fractional Fourier Transform）
標(biāo)簽： 分?jǐn)?shù)階 傅立葉變換
上傳時(shí)間： 2014-01-21
上傳用戶：李彥東
Circular Convolution of two equal-length vectors. Highlights that circular convolution in the time domain is the effectively the same as element-by-element multiplication in the frequency domain.
標(biāo)簽： equal-length Convolution convolution Highlights
上傳時(shí)間： 2014-01-22
上傳用戶：aig85
16點(diǎn)FFT VHDL源程序，The xFFT16 fast Fourier transform (FFT) Core computes a 16-point complex FFT. The input data is a vector of 16 complex values represented as 16-bit 2’s complement numbers – 16-bits for each of the real and imaginary component of a datum.
上傳時(shí)間： 2013-12-20
上傳用戶：yph853211
FRFT時(shí)頻變換代碼（參考算法：H.M. Ozaktas, M.A. Kutay, and G. Bozdagi.Digital computation of the fractional Fourier transform.IEEE Trans. Sig. Proc., 44:2141--2150, 1996.）
標(biāo)簽： H.M. G. M.A. computation
上傳時(shí)間： 2013-12-21
上傳用戶：希醬大魔王
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