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Recursive Fast Fourier Transform Algorithm
, 2008
"... The basis of this report is to cover the Fast Fourier Transform (FFT) algorithm. The Fourier Transform is used mainly in the field of signal processing. The use of the Fourier Transform, and the FFT, is to convert a given input signal from the time domain to the frequency domain. This report will no ..."
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The basis of this report is to cover the Fast Fourier Transform (FFT) algorithm. The Fourier Transform is used mainly in the field of signal processing. The use of the Fourier Transform, and the FFT, is to convert a given input signal from the time domain to the frequency domain. This report
ALGORITHM IN PARALLEL FOR THE FAST FOURIER TRANSFORM
, 2008
"... It has been designed, built and executed a code for the Fast Fourier Transform (FFT), compiled and executed in a cluster of 2n computers under the operating system MacOS and using the routines MacMPI. As practical application, the code has been used to obtain the transformed from an astronomic image ..."
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It has been designed, built and executed a code for the Fast Fourier Transform (FFT), compiled and executed in a cluster of 2n computers under the operating system MacOS and using the routines MacMPI. As practical application, the code has been used to obtain the transformed from an astronomic
The discrete and fast Fourier transforms
, 2012
"... We begin by recalling the familiar definition of the Fourier series. For a periodic function u: [0, 2pi] → C, we define the Fourier transform ûk = ..."
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We begin by recalling the familiar definition of the Fourier series. For a periodic function u: [0, 2pi] → C, we define the Fourier transform ûk =
FFT Fast Fourier Transform
"... Abstract—Spectral warping is a digital signal processing transform which shifts the frequencies contained within a signal along the frequency axis. The Fourier transform coefficients of a warped signal correspond to frequencydomain ‘samples ’ of the original signal which are unevenly spaced along ..."
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Abstract—Spectral warping is a digital signal processing transform which shifts the frequencies contained within a signal along the frequency axis. The Fourier transform coefficients of a warped signal correspond to frequencydomain ‘samples ’ of the original signal which are unevenly spaced along
FAST FOURIER TRANSFORMS
"... on the use of sinusoids to represent temperature distributions. The paper made the controversial claim that any continuous periodic signal could be represented by the sum of properly chosen sinusoidal waves. Among the publication review committee were two famous mathematicians: Joseph Louis Lagrange ..."
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Lagrange, and Pierre Simon de Laplace. Lagrange objected strongly to publication on the basis that Fourier’s approach would not work with signals having discontinuous slopes, such as square waves. Fourier’s work was rejected, primarily because of Lagrange’s objection, and was not published until the death
and Complex Fast Fourier Transforms on
 the Fujitsu VPP 500, Parallel Comput
, 1996
"... If a PC 1 processor was a car, a DSP 2 would be an Indy car. DSPs are everywhere in the world: digital cell phones, broadband modems, digital cameras, MP3 3 players, and on and on. Designing a smart system is a part of the job of an engineer. But creating the prototype 4 that implements this system ..."
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If a PC 1 processor was a car, a DSP 2 would be an Indy car. DSPs are everywhere in the world: digital cell phones, broadband modems, digital cameras, MP3 3 players, and on and on. Designing a smart system is a part of the job of an engineer. But creating the prototype 4 that implements this system is at least, as important. For this reasons, the Master in Electrical Engineering Curriculum introduces DSPs. However, if a teacher wants to traumatize all a generation of students, he can just put them in front of a DSP with on their left, the technical reference, and on their right, a cup of coffee. Indeed, a DSP is mainly controlled thanks to C or assembly code: it is as flexible as awkward. This project created a laboratory prototype. With it, any given student can graphically program a DSP. This prototype is able to perform realtime signal processing algorithms, such as adders, delays, FFTs 5, IIR 6 filters, multipliers but also sampling and feedback operations on a speech signal.
FFT Fast Fourier Transform
"... The appropriate positioning characteristics and fast deployment of Long Term Evolution (LTE) systems makes this technology a promising candidate towards future satellite and terrestrial hybrid scenario. Nevertheless, further studies on the achievable LTE positioning capabilities are still necessary ..."
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The appropriate positioning characteristics and fast deployment of Long Term Evolution (LTE) systems makes this technology a promising candidate towards future satellite and terrestrial hybrid scenario. Nevertheless, further studies on the achievable LTE positioning capabilities are still
� Fast Fourier Transform
"... • Sudden and unexpected death of a baby with no known illness, typically affecting sleeping infants between the ages of two weeks to six months, known as SIDS, is an international phenomena where approximately of 81 cases of SIDS death occurred in Australia during 2010. • Sleep apnea is described as ..."
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• Sudden and unexpected death of a baby with no known illness, typically affecting sleeping infants between the ages of two weeks to six months, known as SIDS, is an international phenomena where approximately of 81 cases of SIDS death occurred in Australia during 2010. • Sleep apnea is described as a sleep disorder caused by abnormal breathing with abnormal pauses occurring for at least 10 seconds and may persist 530 times or more during the sleep period. • Signal at the receiver is fetch into the inphase and quadrature phase (I/Q) demodulator for direct conversion, followed by Data Acquisition System (DAQ) and to be processed with MATLAB for signal processing
Fast Fourier Transform Clustering
"... Based on the assumption that genes having similar expression profiles (coexpressed genes) may be involved in the same biological process, many clustering algorithms have emerged to identify coexpressed genes. The application of clustering techniques to timeseries microarray data is commonly used ..."
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Based on the assumption that genes having similar expression profiles (coexpressed genes) may be involved in the same biological process, many clustering algorithms have emerged to identify coexpressed genes. The application of clustering techniques to timeseries microarray data is commonly used in network and pathway reconstruction. One important information, which is always missing in all clustering algorithms, is the phase information. In network/pathway reconstruction, it is critical to know the order of gene expression. A good clustering algorithm must be able to identify genes that have similar expression profiles including those that are timeshifted or inverted, and provide the information known as phase. The phase information is important to decipher the potential biological relationships between genes, such as the activation, where one expects timeshifted between related expression profiles, and inhibition, where inverted expression relationship is expected. Some well known examples of clustering algorithms include hierarchical clustering, kmean clustering and selforganizing maps. These algorithms use various similarity or dissimilarity measurements, such as Euclidean distance, Pearson correlation coefficient and Spearman rank correlation to score the similarities between gene pairs in the time domain. All these algorithms are unable to identify genes with similar but timeshifted expression patterns. Other clustering approaches such as Bayesian networks, Graph theoretic approaches, Modelbased methods and Fuzzy clustering also lack the ability to address the timeshift problem. Local clustering algorithm [1] used dynamic programming to identify timeshifted genes. However, it fails
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