Sampling theorems for bandlimited random signals in the offset linear canonical transform domain

Sampling theorems for deterministic signals in the offset linear canonical transform (OLCT) domain have been widely proposed in the literature. In this paper, we consider the sampling and reconstruction schemes for random signals in the OLCT domain. We first define the power spectral density and correlation function for random signals in the OLCT domain. By utilizing the definitions, the power spectral density relations for the OLCT filter are derived. Subsequently, the multichannel sampling theorem for bandlimited random signals in the OLCT domain is derived. In addition, some sampling theorems for bandlimited random signals associated with the OLCT are also presented by designing different OLCT filters. Finally, the simulation results are presented to show the advantage and effectiveness of the theorems.     

Convolution,correlation, and sampling theorems for the offset linear canonical transform

The offset linear canonical transform (OLCT), which is a time-shifted and frequency-modulated version of the linear canonical transform, has been shown to be a powerful tool for signal processing and optics. However, some basic results for this transform, such as convolution and correlation theorems, remain unknown. In this paper, based on a new convolution operation, we formulate convolution and correlation theorems for the OLCT. Moreover, we use the convolution theorem to investigate the sampling theorem for the band-limited signal in the OLCT domain. The formulas of uniform sampling and low-pass reconstruction related to the OLCT are obtained. We also discuss the design method of the multiplicative filter in the OLCT domain. Based on the model of the multiplicative filter in the OLCT domain, a practical method to achieve multiplicative filtering through convolution in the time domain is proposed.     

线性正则变换域的带限信号采样理论研究

线性正则变换是傅里叶变换、分数阶傅里叶变换的更广义形式,是一种潜在而重要的信号变换工具,但是与之相应的采样理论目前还不十分完备,所以有必要在线性正则变换域重新研究采样定理.本文从线性正则变换的定义和性质出发,首先得到时域均匀采样信号的线性正则变换;然后在此基础上导出了线性正则变换域带限信号的采样定理和重构公式;最后以chirp信号为例仿真说明了采样定理的应用.文中得出的结论是对经典采样理论的推广,将进一步丰富线性正则变换的理论体系.     

Multichannel Sampling of Signals Band-Limited in Offset Linear Canonical Transform Domains

The aim of the multichannel sampling is the reconstruction of a band-limited signal f(t), from the samples of the responses of M linear time invariant systems, each sampled by the 1/Mth Nyquist rate. As the offset linear canonical transform (OLCT) has been found wide applications in signal processing and optics fields, it is necessary to consider the multichannel sampling based on offset linear canonical transform. In this paper, we develop a multichannel sampling theorem for signals band-limited in offset linear canonical transform domains. Moreover, by designing different OLCT filters, reconstruction formulas for uniform sampling from the signal, from the signal and its first derivative or its generalized Hilbert transform are obtained based on the derived multichannel sampling theorem. Since recurrent nonuniform sampling for the signal has valuable applications, reconstruction expression for recurrent nonuniform samples of the signal band-limited in the offset linear canonical transform domain is also obtained by using the derived multichannel sampling theorem and the properties of the offset linear canonical transform.     

线性正则变换域的框架理论研究

框架理论是研究信号采样特别是非均匀采样问题的一个重要工具,基于框架理论的Gabor展开是在时频混合空间描述信号的非正交展开,而Weyl-Heisenberg框架理论是Gabor展开的理论基础,它描述了信号在时频平面的局部性质与特点,在信号的短时Fourier变换(STFT)、Gabor展开中起到非常重要的作用.本文探讨了W-H框架在线性正则变换下的特点,得到了在时域和线性正则变换域联合空间中信号的展开形式,为在线性正则变换域中讨论信号的展开和非均匀采样问题打下了良好的理论基础.     

About sampling for band-limited linear canonical transform

The linear canonical transform (LCT) is more adapted to many physical problems than the Fourier transform which is a particular case of LCT. The sampling of functions which are band-limited according to some LCT is the topic of many recent papers. This paper shows that classical results can be adapted to obtain errorless reconstruction formulas. The results are provided for usual periodic sampling as well as for periodic nonuniform sampling (PNS) or for irregular sampling.     

A fast algorithm for the linear canonical transform

In recent years there has been a renewed interest in finding fast algorithms to compute accurately the linear canonical transform (LCT) of a given function. This is driven by the large number of applications of the LCT in optics and signal processing. The well-known integral transforms: Fourier, fractional Fourier, bilateral Laplace and Fresnel transforms are special cases of the LCT. In this paper we obtain an O(NlogN) algorithm to compute the LCT by using a chirp-FFT-chirp transformation yielded by a convergent quadrature formula for the fractional Fourier transform. This formula gives a unitary discrete LCT in closed form. In the case of the fractional Fourier transform the algorithm computes this transform for arbitrary complex values inside the unitary circle and not only at the boundary. This chirp-FFT-chirp transform approximates the ordinary Fourier transform more precisely than just the FFT, since it comes from a convergent procedure for non-periodic functions.     

分数阶傅里叶变换域上带通信号的采样定理

傅里叶变换和采样定理是信号处理领域的两大基本问题,采样定理研究了傅里叶变换域上带限信号的采样和重构理论.分数阶傅里叶变换(FRFT)是傅里叶变换的一种推广,与之相应的采样理论目前还不十分完备,所以有必要从FRFT域上重新研究采样定理.本文首先得到了均匀冲激串采样信号的FRFT,然后在此基础上导出了FRFT域上带通信号和低通信号的采样定理和重构公式.这些结果是经典理论的推广,将丰富分数阶傅里叶变换的理论体系.     

Windowed linear canonical transform and its applications

In this paper, we generalize the windowed Fourier transform to the windowed linear canonical transform by substituting the Fourier transform kernel with the linear canonical transform kernel in the windowed Fourier transform definition. It offers local contents, enjoys high resolution, and eliminates cross terms. Some useful properties of the windowed linear canonical transform are derived. Those include covariance property, orthogonality property and inversion formulas. As applications analogues of the Poisson summation formula, sampling formulas and series expansions are given.     

Generalized convolution and product theorems associated with linear canonical transform

The linear canonical transform (LCT), which is a generalized form of the classical Fourier transform (FT), the fractional Fourier transform (FRFT), and other transforms, has been shown to be a powerful tool in optics and signal processing. Many results of this transform are already known, including its convolution theorem. However, the formulation of the convolution theorem for the LCT has been developed differently and is still not having a widely accepted closed-form expression. In this paper, we first propose a generalized convolution theorem for the LCT and then derive a corresponding product theorem associated with the LCT. The ordinary convolution theorem for the FT, the fractional convolution theorem for the FRFT, and some existing convolution theorems for the LCT are shown to be special cases of the derived results. Moreover, some applications of the derived results are presented.     

Image encryption using linear weighted fractional-order transform

As the linear weighted fractional-order Fourier transform (LWFRFT), an extension of the Fourier transform, has been widely studied, many linear weighted fractional-order transforms (LWFRTs) have been proposed consequently. Our research shows that the LWFRT has limitations when applied to image encryption. For example, its application to image encryption leads to the security risks of key invalidation. In this paper, we propose a new reformulation of the LWFRT which establishes the relation between many fractional-order transforms. With the help of the new reformulation, we point out the limitations of the LWFRT and analyze the reasons for key invalidation in image encryption. Finally, numerical simulation verifies our perspective.     

基于分数阶傅里叶变换的多分量Chirp信号的检测与参数估计

分数阶傅里叶变换是傅里叶变换的广义形式。利用Chirp信号在分数阶傅里叶变换域的特点,提出了对含有多个非平稳Chirp成分的信号在噪声中的检测与参数估计方法。理论分析和仿真结果表明,与现有的基于时间域、频率域和时频域的方法相比,该方法物理意义清楚,计算简便,无交叉项干扰,抗噪声性能强。     

A Convolution and Correlation Theorem for the Linear Canonical Transform and Its Application

As a generalization of the fractional Fourier transform (FRFT), the linear canonical transform (LCT) plays an important role in many fields of optics and signal processing. Many properties for this transform are already known, but the correlation theorem, similar to the version of the Fourier transform (FT), is still to be determined. In this paper, firstly, we introduce a new convolution structure for the LCT, which is expressed by a one dimensional integral and easy to implement in filter design. The convolution theorem in FT domain is shown to be a special case of our achieved results. Then, based on the new convolution structure, the correlation theorem is derived, which is also a one dimensional integral expression. Last, as an application, utilizing the new convolution theorem, we investigate the sampling theorem for the band limited signal in the LCT domain. In particular, the formulas of uniform sampling and low pass reconstruction are obtained.     

基于线性正则变换与短时傅里叶变换联合的时频分析方法

线性正则变换作为傅里叶变换、分数阶傅里叶变换更为广义的形式,已经在光学和信号处理等领域得到了应用.短时傅里叶变换是一种线性时频分布,避免了其他双线性时频分布中出现的交叉项干扰,是分析时频信号的有力工具.本文从线性正则变换的定义和性质出发,研究了线性正则变换与短时傅里叶变换的时频关系,提出了基于线性正则变换与短时傅里叶变换联合的时频分析方法,避免了交叉项问题能够实现chirp信号干扰抑制和多分量时频信号分离.最后用仿真实例表明,该方法是分析时频信号的有效手段.     

关于信号tu(t)的傅里叶变换的探讨

傅里叶变换是“信号与线性系统”课程中一个非常重要的教学内容,是理解信号频域特性和进行线性系统频域分析的基础。课程中对于一些不满足绝对可积条件的信号,通过引入广义函数获得了它们的傅里叶变换。斜坡信号tu(t)不是绝对可积的信号,虽然一些文献中给出了它的傅里叶变换表达式,但对于该信号的傅里叶变换是否存在的问题却存在不同观点。论文对斜坡信号傅里叶变换的求解方法进行了研究,指出了常见的错误方法,并对斜坡信号的频率特性给出了一种观点。     

Reduced biquaternion canonical transform, convolution and correlation

The reduced biquaternion canonical transform (RBCT) is defined in this paper, which is the generalization of reduced biquaternion Fourier transform (RBFT). The Parseval's theorem related to RBCT is investigated. The concepts of reduced biquaternion canonical convolution (RBCCV) and reduced biquaternion canonical correlation (RBCCR) are defined, then the convolution and correlation theorem of RBCT are developed in this paper. All these theorems can also be seen as the generalizations of the corresponding theorem related to RBFT. Finally, the discrete form and fast algorithm of RBCT are presented, and the computation complexity is similar to FFT.     

Generalisation of the Dirac-delta impulse extending Laplace and z transform domains

A generalisation of the Dirac-delta impulse and its derivatives as two generalised distributions, namely, the xi and zeta impulses, and their derivatives, defined on the complex s-plane and z-plane of continuous-time and discrete-time functions, respectively, is proposed. The generalised impulses extend the existence of Laplace and z transforms to a large class of infinite duration two-sided functions, which hitherto had no transform or had only a Fourier transform in the form of distributions. The proposed generalised impulses are shown to bridge the gap between the theory of generalised functions and both the unilateral and bilateral Laplace and z transforms. The generalised impulses extend the existence of Laplace and z transforms to include both functions that have a Fourier transform as a distribution as well as exponentially rising infinite duration two-sided functions that have no Fourier transform. It is shown that a modulation theory can now be added to the properties of bilateral transforms. No such theorem has hitherto existed for these transforms. The proposed generalised impulses and the resulting extended Laplace and z transforms are shown to lead to new complex-plane operations, such as spatial convolution, and to simplify operations such as ordinary convolution, sampling and the solution of differential and difference equations. Bilateral Laplace and z transforms may receive greater attention now that these transforms can be applied to a new, large and basic class of functions, such as two-sided infinite duration exponentials and rising trigonometric and hyperbolic functions.     

Algebraic Signal Processing Theory: Sampling for Infinite and Finite 1-D Space

We derive a signal processing framework, called space signal processing, that parallels time signal processing. As such, it comes in four versions (continuous/discrete, infinite/finite), each with its own notion of convolution and Fourier transform. As in time, these versions are connected by sampling theorems that we derive. In contrast to time, however, space signal processing is based on a different notion of shift, called space shift, which operates symmetrically. Our work rigorously connects known and novel concepts into a coherent framework; most importantly, it shows that the sixteen discrete cosine and sine transforms are the space equivalent of the discrete Fourier transform, and hence can be derived by sampling. The platform for our work is the algebraic signal processing theory, an axiomatic approach and generalization of linear signal processing that we recently introduced.     

Sampling and series expansion for linear canonical transform

The linear canonical transform (LCT) has been shown to be a powerful tool for optics and signal processing. This paper investigates new sampling relations in the LCT domain. Firstly, the relationship between linear canonical series (LCS) and LCT is introduced. The LCS expansion coefficients are the sampled values of LCT. Then, based on the conventional Fourier series and LCS, two new sampling relations in the LCT domain are presented, where the signal in the time domain is reconstructed from the samples of its LCT directly. The first theorem considers signals band-limited in some LCT domain, and the second deals with signals band-limited in the conventional Fourier transform domain.     

Local polynomial Fourier transform: A review on recent developments and applications

The local polynomial Fourier transform (LPFT), as a high-order generalization of the short-time Fourier transform (STFT), has been developed and used for many different applications in recent years. This paper attempts to review previous research work on the following issues of the LPFT. Firstly, the definition, the properties of the LPFT and its relationships with other transforms are reviewed. The LPFT for multicomponent signal is then presented. The polynomial time frequency transform (PTFT), which is the maximum likelihood estimator to estimate the parameters in the LPFT, as well as its properties and fast algorithms are discussed. By comparing with the Fourier transform (FT), the STFT and the Wigner-Ville distribution (WVD), the LPFT has its superiority in obtaining improved SNRs, which can be supported by theoretical analysis and computer simulations. Furthermore, the reassignment method is combined with the LPFT and the robust LPFT to improve the concentration of the signal representation in the time-frequency domain. Performances obtained by using various LPP-related methods are compared for signals in different noise environments, such as the additive white Gaussian noise (AGWN), impulsive noise, and the mixture of AGWN and impulsive noise.