Discrete Fourier Transform
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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 TopFarhan Riaz; Mario Dinis Ribeiro; Pedro PimentelNunes; Miguel Tavares Coimbra 2013 IEEE International Conference on Image Processing, 2013
Classification of texture images, especially in cases where the images are subjected to arbitrary rotation and scale changes due to dynamic imaging conditions is a challenging problem in computer vision. This paper proposes a novel methodology to obtain rotation and scale invariant texture features from the images. The feature extraction for a given image involves the calculation of the averages ...
Compressive Data Aggregation from Poisson point process observations
Giancarlo Pastor; Ilkka Norros; Riku Jä ntti; Antonio J. Caamañ o 2015 International Symposium on Wireless Communication Systems (ISWCS), 2015
This paper introduces Stochastic Compressive Data Aggregation (SCDA) for wireless sensor networks (WSN) under random deployments. The Poisson point process (PPP) models the random deployment, and at the same time, allows the efficient implementation of an adequate sparsifying matrix, the random discrete Fourier transform (RDFT). The signal recovery is based on the RDFT which reveals the frequency content of smooth ...
Keith John Jones IET Signal Processing, 2013
The study describes the results of research carried out into the design of a parallel and resourceefficient solution to the realdata polyphase discrete Fourier transform (DFT), or PDFT. The solution is able to exploit both the realvalued nature of the data and the parallel processing capabilities of the computing technology  assumed to be a fieldprogrammable gate array  to ...
Bing Han; Xiqi Gao; Xiaohu You; Jianming Wang; E. Costa Communications, 2003. ICC '03. IEEE International Conference on, 2003
For orthogonal frequencydivision multiplexing (OFDM) systems with pilot symbolaided channel estimation, a straightforward way to overcome system throughput deterioration is by decreasing the power and reducing the number of pilots, which unfortunately, leads directly to the degradation of BER performance. For the purpose of improving the BER performance, an iterative joint channel estimation and symbol detection algorithm with low complexity ...
A tutorial review on discrete fourier transform with data compression application
Chakka Sri Harsha Kaushik; Tadvarthi Gautam; V. Elamaran Green Computing Communication and Electrical Engineering (ICGCCEE), 2014 International Conference on, 2014
This study discuss the hidden facts about the Discrete Fourier Transform (DFT) properties along with the examples. A thorough understanding of the Discrete Time Fourier Transform (DTFT) would become very easy to move on to the DFT in a detailed manner. The extension of onedimensional DFT to twodimensional DFT would be more useful for the twodimensional signals like images. This ...
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Educational Resources on Discrete Fourier Transform
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Farhan Riaz; Mario Dinis Ribeiro; Pedro PimentelNunes; Miguel Tavares Coimbra 2013 IEEE International Conference on Image Processing, 2013
Classification of texture images, especially in cases where the images are subjected to arbitrary rotation and scale changes due to dynamic imaging conditions is a challenging problem in computer vision. This paper proposes a novel methodology to obtain rotation and scale invariant texture features from the images. The feature extraction for a given image involves the calculation of the averages ...
Compressive Data Aggregation from Poisson point process observations
Giancarlo Pastor; Ilkka Norros; Riku Jä ntti; Antonio J. Caamañ o 2015 International Symposium on Wireless Communication Systems (ISWCS), 2015
This paper introduces Stochastic Compressive Data Aggregation (SCDA) for wireless sensor networks (WSN) under random deployments. The Poisson point process (PPP) models the random deployment, and at the same time, allows the efficient implementation of an adequate sparsifying matrix, the random discrete Fourier transform (RDFT). The signal recovery is based on the RDFT which reveals the frequency content of smooth ...
Keith John Jones IET Signal Processing, 2013
The study describes the results of research carried out into the design of a parallel and resourceefficient solution to the realdata polyphase discrete Fourier transform (DFT), or PDFT. The solution is able to exploit both the realvalued nature of the data and the parallel processing capabilities of the computing technology  assumed to be a fieldprogrammable gate array  to ...
Bing Han; Xiqi Gao; Xiaohu You; Jianming Wang; E. Costa Communications, 2003. ICC '03. IEEE International Conference on, 2003
For orthogonal frequencydivision multiplexing (OFDM) systems with pilot symbolaided channel estimation, a straightforward way to overcome system throughput deterioration is by decreasing the power and reducing the number of pilots, which unfortunately, leads directly to the degradation of BER performance. For the purpose of improving the BER performance, an iterative joint channel estimation and symbol detection algorithm with low complexity ...
A tutorial review on discrete fourier transform with data compression application
Chakka Sri Harsha Kaushik; Tadvarthi Gautam; V. Elamaran Green Computing Communication and Electrical Engineering (ICGCCEE), 2014 International Conference on, 2014
This study discuss the hidden facts about the Discrete Fourier Transform (DFT) properties along with the examples. A thorough understanding of the Discrete Time Fourier Transform (DTFT) would become very easy to move on to the DFT in a detailed manner. The extension of onedimensional DFT to twodimensional DFT would be more useful for the twodimensional signals like images. This ...
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IEEEUSA EBooks

SingleTone Parameter Estimation from DiscreteTime Observations
Estimation of the parameters of a singlefrequency complex tone from a finite number of noisy discretetime observations is discussed. The appropriate CramÃ©rRao bounds and maximumlikelihood (ML) estimation algorithms are derived. Some properties of the ML estimators are proved. The relationship of ML estimation to the discrete Fourier transform is exploited to obtain practical algorithms. The threshold effect of one algorithm is analyzed and compared to simulation results. Other simulation results verify other aspects of the analysis.

A Bound on the Output of a Circular Convolution with Application to Digital Filtering
When implementing a digital filter, it is important to utilize in the design a bound or estimate of the largest output value which will be obtained. Such a bound is particularly useful when fixed point arithmetic is to be used since it assists in determining register lengths necessary to prevent overflow. In this paper we consider the class of digital filters which have an impulse response of finite duration and are implemented by means of circular convolutions performed using the discrete Fourier transform. A least upper bound is obtained for the maximum possible output of a circular convolution for the general case of complex input sequences. For the case of real input sequences, a lower bound on the least upper bound is obtained. The use of these results in the implementation of this class of digital filters is discussed.

Data Transmission by FrequencyDivision Multiplexing Using the Discrete Fourier Transform
The Fourier transform data communication system is a realization of frequency division multiplexing (FDM) in which discrete Fourier transforms are computed as part of the modulation and demodulation processes. In addition to eliminating the banks of subcarrier oscillators and coherent demodulators usually required in FDM systems, a completely digital implementation can be built around a specialpurpose computer performing the fast Fourier transform. In this paper, the system is described and the effects of linear channel distortion are investigated. Signal design criteria and equalization algorithms are derived and explained. A differential phase modulation scheme is presented that obviates any equalization.

Fourier Representations of Signals
This chapter contains sections titled: The Fourier Series Cosineonly Expansion of Fourier Series Fourier Series in Complex Exponentials The Fourier Transform Physical Meaning of Fourier Transform Properties of the Fourier Transform Fourier Transform Representations for Periodic Signals The Discrete Fourier Transform The Inverse Discrete Fourier Transform Physical Meaning of the Discrete Fourier Transform This chapter contains sections titled: Further Reading Exercises

This chapter contains sections titled: Goertzel Algorithm Sliding Discrete Fourier Transform (SDFT) SDFT Stability TimeDomain Windowing in the Frequency Domain Sliding Goertzel DFT Conclusions References Appendix

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.

Chapter 2 discusses digital modulation techniques, including both single carrier modulation and multicarrier modulation. Basic OFDM processing operations, such as discrete Fourier transform (DFT)/inverse discrete Fourier transform (IDFT), guard interval insertion/removal, guard band reservation, spectrum shaping, and peaktoaverage power ratio are all addressed.

We have already discovered a rich theory of frequency transforms for analog signals, and this chapter extends the theory to discrete signals. We begin frequency transforms for discrete signals by covering the discrete Fourier transform (DFT). Later, we develop the principles underlying the famous sampling theorem of Shannon and Nyquist. This result effectively builds a frequency analysis bridge between the world of analog signals and the world of discrete signals.

An algorithm is presented for the calculation of the spectrum of direct digital frequency synthesizers (DDFS'B) as a result of phase accumulator truncation. This algorithm. which is derived using number theoretic methods. includes a dosed form expression, relating the magnitude, number, and position of the spurious noise lines in the output spectrum at a DDFS to the readonly memory (ROM) lookup table size, the amount of phase accumulator truncation and the input frequency control command. The combined finite word length effects of the ROM and the DigitaltoAnalog converter (DAC) nonlinearities are also examined in the light of these new results and new design guidelines are developed. The spectrums predicted by these closed form expressions are compared against spectrums generated by a discrete Fourier transform (DFT) and are shown to have comparable accuracy. As a result of obtaining an expression for the magnitude of the spurious noise frequencies, a relationship between the greatest common divisor at the input frequency command word and the ROM table size, the phase accumulator word lengths, and the magnitude of the worst case sput is obtained. This relationship is used as the basis for a novel modification to the conventional phase accumulator structure which results in a 3.922dB reduction in the magnitude of the worst ease spurious response. This hardware modification is also shown to average out the error effects of DAC nonlinearities and roundoff in the stored sine ROM samples.

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.
Standards related to Discrete Fourier Transform
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