改进的离散S变换快速算法与连续小波变换算法性能分析

S变换由于其良好的时频结合特性,在信号处理领域受到了极大重视。本文在综合考虑各种时频方法后,指出了S变换在通信信号侦察处理领域应用的重要性。本文在研究S变换基本原理的基础上,针对目前常用的离散S变换算法进行了分析,指出了其在实现过程中存在的问题,提出了改进的离散S变换快速算法,以减少离散S变换的运算量,实现离散S变换的快速运算。为了验证算法的有效性,本文将离散S变换快速算法、传统离散S变换算法以及连续小波变换,进行了算法性能对比分析和仿真实验。实验结果表明了改进离散S变换快速算法比传统离散S变换算法和连续小波变换在算法的运算量方面要少一至几个数量级,证明了改进算法的有效性。这对于通信信号快速侦察的工程化具有重要的意义。      

Generalized discrete Hartley transforms

The discrete Hartley transform is generalized into four classes in the same way as the generalized discrete Fourier transform. Fast algorithms for the resulting transforms are derived. The generalized transforms are expected to be useful in applications such as digital filter banks, fast computation of the discrete Hartley transform for any composite number of data points, fast computations of convolution, and signal representation. The fast computation of skew-circular convolution by the generalized transforms for any composite number of data points is discussed in detail     

A comparative review of real and complex Fourier-related transforms

Major continuous-time, discrete-time, and discrete Fourier-related transforms as well as Fourier-related series are discussed both with real and complex kernels. The complex Fourier transforms, Fourier series, cosine, sine, Hartley, Mellin, Laplace transforms, and z-transforms are covered on a comparative basis. Generalizations of the Fourier transform kernel lead to a number of novel transforms, in particular, special discrete cosine, discrete sine, and real discrete Fourier transforms, which have already found use in a number of applications. The fast algorithms for the real discrete Fourier transform provide a unified approach for the optimal fast computation of all discrete Fourier-related transforms. The short-time Fourier-related transforms are discussed for applications involving nonstationary signals. The one-dimensional transforms discussed are also extended to the two-dimensional transforms     

一种结构简单的快速W变换算法及其实现

本文给出一种结构简单的快速算法及其“即位”实现程序，用以计算Ｎ＝２＾Ｍ点的所有四种类型的离散Ｗ变换（ＤＷＴ）。该算法所需要的计算量和目前效率最高的ＦＷＴ算法一样，但结构更简单、且使用余弦乘子；因此它既避免了ＦＷＴ算法的缺点，又具有更高的计算效率。     

Split-radix FHT algorithm for real-symmetric data

A fast algorithm for computing the discrete Hartley transform of a real-symmetric data sequence is introduced. The number of computations required is significantly less than that required by the usual split-radix fast Hartley transform.<>     

Relationship between two algorithms for discrete cosine transform

Two contributions are made to the implementation of fast discrete cosine transform algorithms. The first uses Hadamard ordering to improve the regularity of the Lee fast cosine transform (FCT) algorithm for the discrete cosine transform (DCT). The second derives a close relationship between the Lee FCT and the recursive algorithm for the DCT.<>     

Reconstruction of a compactly supported function from the discretesampling of its Fourier transform

We derive a new relation between the discrete Fourier transform of a discrete sampling set of a compactly supported function and its Fourier transform. From this relation, we obtain a new window function. We then propose a new efficient algorithm to reconstruct the original function from the discrete sampling of its Fourier transform, which can adopt the fast Fourier transform and has much better accuracy than those in the literature. Several numerical experiments are also provided, illustrating the results     

What is the fast Fourier transform?

The fast Fourier transform is a computational tool which facilitates signal analysis such as power spectrum analysis and filter simulation by means of digital computers. It is a method for efficiently computing the discrete Fourier transform of a series of data samples (referred to as a time series). In this paper, the discrete Fourier transform of a time series is defined, some of its properties are discussed, the associated fast method (fast Fourier transform) for computing this transform is derived, and some of the computational aspects of the method are presented. Examples are included to demonstrate the concepts involved.     

Fast algorithms for the computation of sliding discrete sinusoidal transforms

Fast algorithms for computing various discrete cosine transforms and discrete sine transforms in a sliding window are proposed. The algorithms are based on a recursive relationship between three subsequent local transform spectra. Efficient inverse algorithms for signal processing in a sliding window are also presented. The computational complexity of the algorithms is compared with that of known fast discrete sinusoidal transforms and running recursive algorithms.     

Fast interpolation algorithm using fast Hartley transform

The use of fast Hartley transform for fast discrete interpolation is considered. The computational method uses the sprit-radix algorithm which requires the least number of operations compared with other Hartley algorithms. Results from this method are compared with those using the fast Fourier transform.     

Fast Hartley transform algorithm

The discrete Hartley transform is a new tool for the analysis, design and implementation of digital signal processing algorithms and systems. It is strictly symmetrical concerning the transformation and its inverse. A new fast Hartley transform algorithm has been developed. Applied to real signals, it is faster than a real fast Fourier transform, especially in the case of the inverse transformation. The speed of operation for a fast convolution can thus be increased.     

Novel DCT-Based Real-Valued Discrete Gabor Transform and Its Fast Algorithms

The oversampled Gabor transform is more effective than the critically sampled one in many applications. The biorthogonality relationship between the analysis window and the synthesis window of the Gabor transform represents the completeness condition. However, the traditional discrete cosine transform (DCT)-based real-valued discrete Gabor transform (RGDT) is available only in the critically sampled case and its biorthogonality relationship for the transform has not been unveiled. To bridge these important gaps, this paper proposes a novel DCT-based RDGT, which can be applied in both the critically sampled case and the oversampled case, and their biorthogonality relationships can be derived. The proposed DCT-based RDGT involves only real operations and can utilize fast DCT algorithms for computation, which facilitates computation and implementation by hardware or software as compared to that of the traditional complex-valued discrete Gabor transform. This paper also develops block time-recursive algorithms for the efficient and fast computation of the RDGT and its inverse transform. Unified parallel lattice structures for the implementation of these algorithms are presented. Computational complexity analysis and comparisons have shown that the proposed algorithms provide a more efficient and faster approach for discrete Gabor transforms as compared to those of the existing discrete Gabor transform algorithms. In addition, an application in the noise reduction of the nuclear magnetic resonance free induction decay signals is presented to show the efficiency of the proposed RDGT for time-frequency analysis.      

Algorithmes de transformations de Fourier et en cosinus mono et bidimensionnels

This paper presents a fast algorithm for the computation of the discrete Fourier and cosine transform, and this for transform lengths which are powers of 2. This approach achieves the lowest known number of operations (multiplications and additions) for the discrete Fourier transform of real, complex, symmetrical and antisymmetrical sequences, for the odd discrete Fourier transform and for the discrete cosine transform. The extension to the two-dimensional Fourier and cosine transform is presented as well.     

Multiparameter discrete transforms based on discrete orthogonal polynomials and their application to image watermarking

Applications of discrete orthogonal polynomials (DOPs) in image processing have been recently emerging. In particular, Krawtchouk, Chebyshev, and Charlier DOPs have been applied as bases for image analysis in the frequency domain. However, fast realizations and fractional-type generalizations of DOP-based discrete transforms have been rarely addressed. In this paper, we introduce families of multiparameter discrete fractional transforms via orthogonal spectral decomposition based on Krawtchouk, Chebyshev, and Charlier DOPs. The eigenvalues are chosen arbitrarily in both unitary and non-unitary settings. All families of transforms, for varieties of eigenvalues, are applied in image watermarking. We also exploit recently introduced fast techniques to reduce complexity for the Krawtchouk case. Experimental results show the robustness of the proposed transforms against watermarking attacks.     

Compact non-binary fast adders using single-electron devices

This paper proposes compact adders that are based on non-binary redundant number systems and single-electron (SE) devices. The adders use the number of single electrons to represent discrete multiple-valued logic state and manipulate single electrons to perform arithmetic operations. These adders have fast speed and are referred as fast adders. We develop a family of SE transfer circuits based on MOSFET-based SE turnstile. The fast adder circuit can be easily designed by directly mapping the graphical counter tree diagram (CTD) representation of the addition algorithm to SE devices and circuits. We propose two design approaches to implement fast adders using SE transfer circuits: the threshold approach and the periodic approach. The periodic approach uses the voltage-controlled single-electron transfer characteristics to efficiently achieve periodic arithmetic functions. We use HSPICE simulator to verify fast adders operations. The speeds of the proposed adders are fast. The numbers of transistors of the adders are much smaller than conventional approaches. The power dissipations are much lower than CMOS and multiple-valued current-mode fast adders.     

The fast Fourier transform

The fast Fourier transform (FFT), a computer algorithm that computes the discrete Fourier transform much faster than other algorithms, is explained. Examples and detailed procedures are provided to assist the reader in learning how to use the algorithm. The savings in computer time can be huge; for example, an N = 210-point transform can be computed with the FFT 100 times faster than with the use of a direct approach.     

二维实值离散Gabor变换时间递归算法的双层并行格型结构实现方法

本文首先简单回顾了作者曾提出的二维实值离散Gabor变换及其与复值离散Gabor变换的简单关系，然后着重探讨了二维实值离散Gabor变换快速计算问题，提出了二维实值离散Gabor变换系数求解的时间递归算法以及由变换系数重构原图像的块时间递归算法，研究了双层并行格型结构实现算法的方法，计算复杂性分析及与其它算法的比较证明了双层并行格型结构实现方法在实时处理方面的优越性。     

Spectral interpretation of the fast tabular technique for fixed-polarity Reed-Muller expressions

This paper presents a uniform spectral approach to the fast tabular technique for generating fixed polarity Reed–Muller expressions. Basic operations in the tabular technique are described through the discrete dyadic convolution. The presented results can be extended to various polynomial expansions of discrete functions.     

基2DFT的最快速算法

本文提出一种FFT新算法,其计算量不大于现有的各种基2DFT算法.然后,与Winograd小DFT(4,8,16点)结合使用,得出一种计算DFT的最快速算法.     

基于广义XTR体制的签名方案

与RSA和ECC相比较,同等安全程度下XTR密钥长度远远小于RSA,最多只是ECC密钥长度的2倍;而XTR参数和密钥选取远远快于ECC。该文利用有限域中元素迹的快速算法,给出了两种特殊的基于广义XTR体制的签名方案,其安全性等价于解广义XTR群中的离散对数困难问题,但是传输的数据量只有原来方案的1/3.