Non-uniform discrete Fourier transform

About: Non-uniform discrete Fourier transform is a research topic. Over the lifetime, 4067 publications have been published within this topic receiving 123952 citations.

A Generalization of the Fast Fourier Transform

Abstract: A procedure for factoring of the N×N matrix representing the discrete Fourier transform is presented which does not produce shuffled data. Exactly one factor is produced for each factor of N, resulting in a fast Fourier transform valid for any N. The factoring algorithm enables the fast Fourier transform to be implemented in general with four nested loops, and with three loops if N is a power of two. No special logical organization, such as binary indexing, is required to unshuffle data. Included are two sample programs, one which writes the equations of the matrix factors employing the four key loops, and one which implements the algorithm in a fast Fourier transform for N a power of two. The algorithm is shown to be most efficient for Na power of two.

Fractional Fourier transform of Lorentz-Gauss beams

Abstract: Lorentz-Gauss beams are introduced to describe certain laser sources that produce highly divergent beams. The fractional Fourier transform (FRFT) is applied to treat the propagation of Lorentz-Gauss beams. Based on the definition of convolution and the convolution theorem of the Fourier transform, an analytical expression for a Lorentz-Gauss beam passing through an FRFT system has been derived. By using the derived expression, the properties of a Lorentz-Gauss beam in the FRFT plane are graphically illustrated with numerical examples.

The Fast Fourier-Hadamard Transform and Its Use in Signal Representation and Classification,

Abstract: : A discrete time transform was studied and applied to the representation and discrimination of digitized signals. The transform consists of an orthogonal (Hadamard) matrix whose elements are all ones and minus ones. To facilitate implementation, a fast Hadamard transform (FHT) has been developed requiring only NlogN rather than N squared algebraic additions. Several properties of the FHT are revealed, including the nature of its presence in the fast Fourier transform, in which it performs the additive operations as shown by further decomposing the product of matrices representing the FFT.

Computer Explorations in Signals and Systems Using MATLAB

Abstract: 1. Signals and Systems. Tutorial: Basic MATLAB Functions for Representing Signals. Discrete-Time Sinusoidal Signals. Transformations of the Time Index for Discrete-Time Signals. Properties of Discrete-Time Systems. Implementing a First-Order Difference Equation. Continuous-Time Complex Exponential Signals. Transformations of the Time Index for Continuous-Time Signals. Energy and Power for Continuous-Time Signals. 2. Linear Time-Invariant Systems. Tutorial: conv. Tutorial: filter. Tutorial: lsim with Differential Equations. Properties of Discrete-Time LTI Systems. Linearity and Time-Invariance. Noncausal Finite Impulse Response Filters. Discrete-Time Convolution. Numerical Approximations of Continuous-Time Convolution. The Pulse Response of Continuous-Time LTI Systems. Echo Cancellation via Inverse Filtering. 3. Fourier Series Representation of Periodic Signals. Tutorial: Computing the Discrete-Time Fourier Series with fft. Tutorial: freqz. Tutorial: lsim with System Functions. Eigenfunctions of Discrete-Time LTI Systems. Synthesizing Signals with the Discrete-Time Fourier Series. Properties of the Continuous-Time Fourier Series. Energy Relations in the Continuous-Time Fourier Series. First-Order Recursive Discrete-Time Filters. Frequency Response of a Continuous-Time System. Computing the Discrete-Time Fourier Series. Synthesizing Continuous-Time Signals with the Fourier Series. The Fourier Representation of Square and Triangle Waves. Continuous-Time Filtering. 4. The Continuous-Time Fourier Transform. Tutorial: freqs. Numerical Approximation to the Continuous-Time Fourier Transform. Properties of the Continuous-Time Fourier Transform. Time- and Frequency-Domain Characterizations of Systems. Impulse Responses of Differential Equations by Partial Fraction Expansion. Amplitude Modulation and the Continuous-Time Fourier Transform. Symbolic Computation of the Continuous-Time Fourier Transform. 5. The Discrete-Time Fourier Transform. Computing Samples of the DTFT. Telephone Touch-Tone. Discrete-Time All-Pass Systems. Frequency Sampling: DTFT-Based Filter Design. System Identification. Partial Faction Expansion for Discrete-Time Systems. 6. Time and Frequency Analysis of Signals and Systems. A Second-Order Shock Absorber. Image Processing with One-Dimensional Filters. Filter Design by Transformation. Phase Effects for Lowpass Filters. Frequency Division Multiple-Access. Linear Prediction on the Stock Market. 7. Sampling. Aliasing due to Undersampling. Signal Reconstruction from Samples. Upsampling and Downsampling. Bandpass Sampling. Half-Sample Delay. Discrete-Time Differentiation. 8. Communications Systems. The Hilbert Transform and Single-Sideband AM. Vector Analysis of Amplitude Modulation with Carrier. Amplitude Demodulation and Receiver Synchronization. Intersymbol Interference in PAM Systems. Frequency Modulation. 9. The Laplace Transform. Tutorial: Making Continuous-Time Pole-Zero Diagrams. Pole Locations for Second-Order Systems. Butterworth Filters. Surface Plots of Laplace Transforms. Implementing Noncausal Continuous-Time Filters. 10. The z-Transform. Tutorial: Making Discrete-Time Pole-Zero Diagrams. Geometric Interpretation of the Discrete-Time Frequency Response. Quantization Effects in Discrete-Time Filter Structures. Designing Discrete-Time Filters with Euler Approximations. Discrete-Time Butterworth Filter Design Using the Bilinear Transformation. 11. Feedback Systems. Feedback Stabilization: Stick Balancing. Stabilization of Unstable Systems. Using Feedback to Increase the Bandwidth of an Amplifier. Bibliography. Index.