Discrete Fourier Transform
9,596 resources related to Discrete Fourier Transform
IEEE Organizations related to Discrete Fourier Transform
Back to TopConferences related to Discrete Fourier Transform
Back to Top2012 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
he International Conference on Digital Image Computing: Techniques and Applications (DICTA) is the main Australian Conference on computer vision, image processing, pattern recognition, and related areas. DICTA was established as a biannual conference in 1991 and became an annual event in 2007. It is the premiere conference of the Australian Pattern Recognition Society (APRS).
Periodicals related to Discrete Fourier Transform
Back to TopImage Processing, IEEE Transactions on
Signalprocessing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital halftoning and display, andcolor reproduction.
The most highlycited general interest journal in electrical engineering and computer science, the Proceedings is the best way to stay informed on an exemplary range of topics. This journal also holds the distinction of having the longest useful archival life of any EE or computer related journal in the world! Since 1913, the Proceedings of the IEEE has been the ...
Signal Processing Letters, IEEE
Rapid dissemination of new results in signal processing worldwide.
Signal Processing, IEEE Transactions on
The technology of transmission, recording, reproduction, processing, and measurement of speech; other audiofrequency waves and other signals by digital, electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of thesetechnologies.
Xplore Articles related to Discrete Fourier Transform
Back to TopA fast d.f.t. algorithm using complex integer transforms
I. S. Reed; T. K. Truong Electronics Letters, 1978
For certain large transform lengths, Winograd's algorithm for computing the discrete Fourier transform (d.f.t.) is extended considerably. This is accomplished by performing the cyclic convolution, required by Winograd's method, by a fast transform over certain complex integer fields developed previously by the authors. This new algorithm requires fewer multiplications than either the standard fast Fourier transform (f.f.t.) or Winograd's more ...
Richard C. Hendriks; Richard Heusdens; Jesper Jensen IEEE Transactions on Audio, Speech, and Language Processing, 2007
Although many discrete Fourier transform (DFT) domainbased speech enhancement methods rely on stochastic models to derive clean speech estimators, like the Gaussian and Laplace distribution, certain speech sounds clearly show a more deterministic character. In this paper, we study the use of a deterministic model in combination with the wellknown stochastic models for speech enhancement. We derive a minimum meansquare ...
Lorenzo Picinali; Charalambos Chrysostomou; Huseyin Seker Proceedings of 2012 IEEEEMBS International Conference on Biomedical and Health Informatics, 2012
Transforming proteins into signals, and analyzing their spectra using signal processing techniques (e.g., the Discrete Fourier Transform), has proven to be a suitable method for extracting information about the protein's biological functions. Along with imaging, sound is always found to be one of the helpful tools that have been used to characterize and distinguish objects, particularly, in medicine and biology. ...
Minkyu Sung; Jaehoon Lee; Jichai Jeong IET Communications, 2014
The authors propose a novel localised discrete Fourier transform (DFT) spread _M_ary amplitude shift keying (_M_ASK) orthogonal frequency division multiplexing (OFDM) system with the Hermitian symmetry (DFTspread _M_ASK HS OFDM) to reduce the peaktoaverage power ratio (PAPR). Compared with the conventional OFDM and localised DFTspread OFDM, the proposed system has lower PAPR not only because of the DFTspread scheme but ...
Highperformance RDFT design for applications of digital radio mondiale
ShinChi Lai; WenHo Juang; YuehShu Lee; SheauFang Lei 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013
This paper presents a novel recursive discrete Fourier transform (RDFT) integrated with prime factor and common factor decomposition algorithms. For audio decoder and orthogonal frequencydivision multiplexing (OFDM) in a DRM receiver, the proposed RDFT processor is applied to compute both DFT and IMDCT coefficients. Hence, it can greatly reduce the hardware costs in implementation of a portable DRM receiver. For ...
More Xplore Articles
Educational Resources on Discrete Fourier Transform
Back to TopeLearning
A fast d.f.t. algorithm using complex integer transforms
I. S. Reed; T. K. Truong Electronics Letters, 1978
For certain large transform lengths, Winograd's algorithm for computing the discrete Fourier transform (d.f.t.) is extended considerably. This is accomplished by performing the cyclic convolution, required by Winograd's method, by a fast transform over certain complex integer fields developed previously by the authors. This new algorithm requires fewer multiplications than either the standard fast Fourier transform (f.f.t.) or Winograd's more ...
Richard C. Hendriks; Richard Heusdens; Jesper Jensen IEEE Transactions on Audio, Speech, and Language Processing, 2007
Although many discrete Fourier transform (DFT) domainbased speech enhancement methods rely on stochastic models to derive clean speech estimators, like the Gaussian and Laplace distribution, certain speech sounds clearly show a more deterministic character. In this paper, we study the use of a deterministic model in combination with the wellknown stochastic models for speech enhancement. We derive a minimum meansquare ...
Lorenzo Picinali; Charalambos Chrysostomou; Huseyin Seker Proceedings of 2012 IEEEEMBS International Conference on Biomedical and Health Informatics, 2012
Transforming proteins into signals, and analyzing their spectra using signal processing techniques (e.g., the Discrete Fourier Transform), has proven to be a suitable method for extracting information about the protein's biological functions. Along with imaging, sound is always found to be one of the helpful tools that have been used to characterize and distinguish objects, particularly, in medicine and biology. ...
Minkyu Sung; Jaehoon Lee; Jichai Jeong IET Communications, 2014
The authors propose a novel localised discrete Fourier transform (DFT) spread _M_ary amplitude shift keying (_M_ASK) orthogonal frequency division multiplexing (OFDM) system with the Hermitian symmetry (DFTspread _M_ASK HS OFDM) to reduce the peaktoaverage power ratio (PAPR). Compared with the conventional OFDM and localised DFTspread OFDM, the proposed system has lower PAPR not only because of the DFTspread scheme but ...
Highperformance RDFT design for applications of digital radio mondiale
ShinChi Lai; WenHo Juang; YuehShu Lee; SheauFang Lei 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013
This paper presents a novel recursive discrete Fourier transform (RDFT) integrated with prime factor and common factor decomposition algorithms. For audio decoder and orthogonal frequencydivision multiplexing (OFDM) in a DRM receiver, the proposed RDFT processor is applied to compute both DFT and IMDCT coefficients. Hence, it can greatly reduce the hardware costs in implementation of a portable DRM receiver. For ...
More eLearning Resources
IEEE.tv Videos
Recent Developments in the Sparse Fourier Transform
President Karen Bartleson Noted Speaker at Transform Africa Smart Africa Women's Summit
High Frequency Magnetic Circuit Design for Power Electronics
2015 IEEE Honors: IEEE Richard W. Hamming Medal  Imre Csiszar
Where's my electric car?
Worms, Waves, and Robots
IMS 2011 Microapps  A MultiLevel Conductor Surface Roughness Model
Volunteers: The IEEE Perpetual Power Source
Mouser Electronics Warehouse Tour with Grant Imahara
Microfluidic diagnostics and other breakthrough technologies.
EMBC 2011Speaker HighlightsMary Tolikas, PhD, MBA
MicroApps 2013: Design and Simulation of Phased Arrays in VSS
Build Your Career: IEEE Metro Area Workshops
WIRELESS TRANSCEIVER SYSTEM DESIGN FOR MODERN COMMUNICATION STANDARDS
Transportation Electrification: San Diego Gas & Electric's Implementation of the SmartGrid
Life Sciences: Surface Enhanced Raman Spectroscopy, and more
IEEE EMBS Unconference on Rehabilitation Robotics
Karen Bartleson  Standards Education 3 of 3  IEEESA
Conquering the CoFounder Quest: N3XT Finding Your Founder Niche Series
IEEEUSA EBooks

Fourier Transform and Fourier Series
The Fourier transform (FT) has been widely used in circuit analysis and synthesis, from filter design to signal processing, image reconstruction, and so on. Fourier transform is used for energy signal which contain finite energy. The discrete Fourier transform (DFT) and fast Fourier transform (FFT) are discrete tools to analyze time domain signals. One needs to know the problems caused by discretization and specify the parameters accordingly to avoid nonphysical and nonmathematical results. Mathematically, FT is defined for continuous time signals, and in order to go to frequency domain, the time signal must be observed from an infiniteextend time window. This chapter lists a simple MATLAB code for the Fourier series representation of a given function. The number of terms required in the Fourier series representation depends on the smoothness of the function and the specified accuracy.

This book is Volume IV of the series DSP for MATLAB™ and LabVIEW™. Volume IV is an introductory treatment of LMS Adaptive Filtering and applications, and covers cost functions, performance surfaces, coefficient perturbation to estimate the gradient, the LMS algorithm, response of the LMS algorithm to narrowband signals, and various topologies such as ANC (Active Noise Cancelling) or system modeling, Noise Cancellation, Interference Cancellation, Echo Cancellation (with single and dualH topologies), and Inverse Filtering/Deconvolution. The entire series consists of four volumes that collectively cover basic digital signal processing in a practical and accessible manner, but which nonetheless include all essential foundation mathematics. As the series title implies, the scripts here will run on both MATLAB™ and LabVIEW™. The text for all volumes contains many examples, and many useful computational scripts, augmented by demonstration scripts and LabVIEW&# 482; Virtual Instruments (VIs) that can be run to illustrate various signal processing concepts graphically on the user's computer screen. Volume I consists of four chapters that collectively set forth a brief overview of the field of digital signal processing, useful signals and concepts (including convolution, recursion, difference equations, LTI systems, etc), conversion from the continuous to discrete domain and back (i.e., analogtodigital and digitaltoanalog conversion), aliasing, the Nyquist rate, normalized frequency, sample rate conversion and Mulaw compression, and signal processing principles including correlation, the correlation sequence, the Real DFT, correlation by convolution, matched filtering, simple FIR filters, and simple IIR filters. Chapter 4 of Volume I, in particular, provides an intuitive or "first principle" understanding of how digital filtering and frequency transforms work. Volume II provides detailed coverage of discrete frequency transforms, includi g a brief overview of common frequency transforms, both discrete and continuous, followed by detailed treatments of the Discrete Time Fourier Transform (DTFT), the zTransform (including definition and properties, the inverse ztransform, frequency response via ztransform, and alternate filter realization topologies including Direct Form, Direct Form Transposed, Cascade Form, Parallel Form, and Lattice Form), and the Discrete Fourier Transform (DFT) (including Discrete Fourier Series, the DFTIDFT pair, DFT of common signals, bin width, sampling duration, and sample rate, the FFT, the Goertzel Algorithm, Linear, Periodic, and Circular convolution, DFT Leakage, and computation of the Inverse DFT). Volume III covers digital filter design, including the specific topics of FIR design via windowedideallowpass filter, FIR highpass, bandpass, and bandstop filter design from windowedideal lowpass filters, FIR design using the transition bandoptimized Frequency Sampling technique (impleme ted by InverseDFT or Cosine/Sine Summation Formulas), design of equiripple FIRs of all standard types including Hilbert Transformers and Differentiators via the Remez Exchange Algorithm, design of Butterworth, Chebyshev (Types I and II), and Elliptic analog prototype lowpass filters, conversion of analog lowpass prototype filters to highpass, bandpass, and bandstop filters, and conversion of analog filters to digital filters using the Impulse Invariance and Bilinear Transform techniques. Certain filter topologies specific to FIRs are also discussed, as are two simple FIR types, the Comb and Moving Average filters. Table of Contents: Introduction To LMS Adaptive Filtering / Applied Adaptive Filtering

This chapter contains sections titled: Properties of the Fourier Transformation Spectrum of Example Time Domain Signals Transformation of Sampled Time Signals Short Time Fourier Transform of Continuous Signals Discrete Fourier Transform

Transforms Used in Electronic Image Processing
This chapter contains sections titled: The Fourier Series The OneDimensional Fourier Transform The TwoDimensional Fourier Transform Important Functions Relating to the Fourier Transform The Discrete Fourier Transform Example and Properties of the Discrete Fourier Transform Computation of the Discrete Fourier Transform Other Image Transforms

This chapter contains sections titled: Introduction Discrete Fourier Transform (DFT) Filter Bank L Band Filters (Revisited) Quadrature Mirror Filter (QMF) Polyphase Representation Frequency Masking Filters Cascaded IntegratorComb (CIC) Filter

Measurement of Frequency Response Functions  Standard Solutions
This chapter contains sections titled: Introduction An Introduction to the Discrete Fourier Transform Spectral Representations of Periodic Signals Analysis of FRF Measurements Using Periodic Excitations Reducing FRF Measurement Errors for Periodic Excitations FRF Measurements Using Random Excitations FRF Measurements of MultipleInput, MultipleOutput Systems Guidelines for FRF Measurements Conclusion Exercises Appendixes

Analysis and Simulation of a Digital Mobile Channel Using Orthogonal Frequency Division Multiplexing
This paper discusses the analysis and simulation of a technique for combating the effects of multipath propagation and cochannel interference on a narrow band digital mobile channel. This system uses the discrete Fourier transform to orthogonally frequency multiplex many narrow subchannels, each signaling at a very low rate, into one highrate channel. When this technique is used with pilotbased correction, the effects of flat Rayleigh fading can be reduced significantly. An improvement in signaltointerference ratio of 6 dB can be obtained over the bursty Rayleigh channel. In addition, with each subchannel signaling at a low rate, this technique can provide added protection against delay spread. To enhance the behavior of the technique in a heavily frequency selective environment, interpolated pilots are used. A frequency offset reference scheme is employed for the pilots to improve protection against cochannel interference.

This chapter contains sections titled: Image Coordinate System Linear Systems Point Source and Impulse Functions Probability and Random Variable Functions Image Formation Pinhole Imaging Fourier Transform Radon Transform Sampling Discrete Fourier Transform Wavelet Transform Exercises References

More on OneDimensional Simulation
This chapter introduces some advanced concepts of onedimensional electromagnetic (EM) FDTD simulation. First, it changes the formulation slightly and introduces the use of the flux density into the simulation. One of the most significant developments in the FDTD method is a means to simulate frequencydependent dielectric materials. Then, the chapter introduces the use of the discrete Fourier transform in FDTD simulation. This is an extremely powerful method to quantify the output of the simulation. The chapter concludes with the simulation of human muscle tissue. Muscle tissue can be adequately simulated over a frequency range of about two decades with the Lorentz formulation.

You can immediately have the power to perform electromagnetic simulation. If you have a fundamental understanding of electromagnetic theory and the knowledge of at least one highlevel computer language, you can begin writing simple electromagnetic simulation programs after reading the first chapter of this book. Electromagnetic Simulation Using the FDTD Method describes the power and flexibility of the finitedifference timedomain method as a direct simulation of Maxwell's equations. The FDTD method takes advantage of today's advanced computing power because its computational requirements increase linearly with the size of the simulation problem. This book begins with a simple onedimensional simulation and progresses to a threedimensional simulation. Each chapter contains a concise explanation of an essential concept and instruction on its implementation into computer code. Projects that increase in complexity are included, ranging from simulations in free space to propagation in dispersive media. Peripheral topics that are pertinent to timedomain simulation, such as Ztransforms and the discrete Fourier transform, are also covered. Electromagnetic Simulation Using the FDTD Method is written for anyone who would like to learn electromagnetic simulation using the finitedifference timedomain method. Appropriate as both a textbook and for selfstudy, this tutorialstyle book will provide all the background you will need to begin research or other practical work in electromagnetic simulation.
Standards related to Discrete Fourier Transform
Back to TopNo standards are currently tagged "Discrete Fourier Transform"