用时域谐波定标的数字语音编码

本文给出了一种以9.6Kb/s数据率实时工作的新的数字语音编码器.该系统由时域谐波定标(TDHS)及子频带编码(SBC)两种不同的语音压缩算法组成.阐述了TDHS的基本原理,简述了几种不同的音调检测方法.本文最后对用DSP硬件实时执行该系统的几种方式作了讨论.     

Almost-sure identifiability of multidimensional harmonic retrieval

Two-dimensional (2-D) and, more generally, multidimensional harmonic retrieval is of interest in a variety of applications, including transmitter localization and joint time and frequency offset estimation in wireless communications. The associated identifiability problem is key in understanding the fundamental limitations of parametric methods in terms of the number of harmonics that can be resolved for a given sample size. Consider a mixture of 2-D exponentials, each parameterized by amplitude, phase, and decay rate plus frequency in each dimension. Suppose that I equispaced samples are taken along one dimension and, likewise, J along the other dimension. We prove that if the number of exponentials is less than or equal to roughly IJ/4, then, assuming sampling at the Nyquist rate or above, the parameterization is almost surely identifiable. This is significant because the best previously known achievable bound was roughly (I+J)/2. For example, consider I=J=32; our result yields 256 versus 32 identifiable exponentials. We also generalize the result to N dimensions, proving that the number of exponentials that can be resolved is proportional to total sample size     

Improved Newton-type algorithm for adaptive implementation ofPisarenko's harmonic retrieval method and its convergence analysis

Pisarenko's harmonic retrieval (PHR) method is probably the first eigenstructure based algorithm for estimating the frequencies of sinusoids corrupted by additive white noise. To develop an adaptive implementation of the PHR method, one group of authors has proposed a least-squares type recursive algorithm. In their algorithm, they made approximations for both gradient and Hessian. The authors derive an improved algorithm, where they use exact gradient and a different approximation for the Hessian and analyze its convergence rigorously. Specifically, they provide a proof for the local convergence and detailed arguments supporting the local instability of undesired stationary points. Computer simulations are used to verify the convergence performance of the new algorithm. Its performance is substantially better than that exhibited by its counterpart, especially at low SNR's     

Cumulant-based approach to harmonic retrieval and related problems

A frequently encountered problem in signal processing is that of estimating the frequencies and amplitudes of harmonics observed in additive colored Gaussian noise. In practice, the observed signals are contaminated with spatially and temporally colored noise of unknown power spectral density. A cumulant-based approach to these problems is proposed. The cumulants of complex processes are defined, and it is shown that specific 1-D slices of the fourth-order cumulant of the noisy signal for the direction of arrival (DOA) and retrieval of harmonics in noise (RHN) problems are identical to the autocorrelation of a related noiseless signal. Hence correlation-based high-resolution methods may be used with fourth-order cumulants as well. The effectiveness of the proposed methods is demonstrated through standard simulation examples     

Two-dimensional time-domain inverse scattering for quantitative analysis of breast composition

Forward-backward time-stepping is a unique approach for solving electromagnetic inverse scattering problems in the time domain. In this paper, the technique is applied to a realistic, heterogeneous breast model. The ability to detect a 5-mm diameter malignancy and provide substantial quantitative information about the breast's composition is demonstrated.     

NEW APPROACH TO HARMONIC RETRIEVAL IN NOISE

This paper addresses the harmonic retrieval problem in non-Gaussian ARMA noise. A hybrid ESPRIT approach using second-and third-order statistics is proposed. First, third-order statistics are used to identify the AR part of the non-Gaussian noise process, then the noisy measurements are filtered by AR polynomial, finally, the harmonic signal parameters are estimated. Simulation examples show the effectiveness and high resolution of the new approach.     

2-D harmonic retrieval using higher-order statistics

We consider the problem of estimating the harmonics of a noisy 2-D signal. The observed data is modeled as a 2-D sinusoidal signal, with either random or deterministic phases, plus additive Gaussian noise ofunknown covariance. Our method utilizes recently defined higher-order statistics, referred to as mixed-cumulants, which permit a formulation that is applicable to both the random and deterministic case. In particular, we first estimate the frequencies in each dimension using an overdetermined Yule-Walker type approach. Then, the 1-D frequencies are paired using a matching criterion. To support our theory, we examine the performance of the proposed method via simulations.     

A harmonic retrieval framework for discontinuous motion estimation

Motion discontinuities arise when there are occlusions or multiple moving objects in the scene that is imaged. Conventional regularization techniques use smoothness constraints but are not applicable to motion discontinuities. In this paper, we show that discontinuous (or multiple) motion estimation can be viewed as a multicomponent harmonic retrieval problem. From this viewpoint, a number of established techniques for harmonic retrieval ran be applied to solve the challenging problem of discontinuous (or multiple) motion. Compared with existing techniques, the resulting algorithm is not iterative, which not only implies computational efficiency but also obviates concerns regarding convergence or local minima. It also adds flexibility to spatio-temporal techniques which have suffered from lack of explicit modeling of discontinuous motion. Experimental verification of our framework on both synthetic data as well as real image data is provided.     

Statistical analysis of state-space approach in harmonic retrieval

The author presents a statistical analysis of the performance of the state-variable balancing for estimating the parameters of exponential signals in the presence of additive noise. The case of frequency estimation for a single damped sinusoid is carried out in detail because the analysis can be presented more clearly; the formulas are simpler and provide insight; and the results are applicable in radar, sonar, communication, and data modelling. Analytical expressions for the variances of the frequency estimate at high signal-to-noise ratios is derived. Both analytical and experimental results are presented to illustrate the performance of the state-variable balancing method     

谐波环境下基于时域特性分析的电能质量评估

在谐波环境下,电能质量容易发生畸变,电力系统极其不稳定,该研究采用时域特性分析的方法,构建出改进型的电能质量扰动分析模型.该模型能够提取电能扰动特征量、基波幅值变化特征量和加性扰动特征量等,通过Daubechies小波变换实现信号的放大,并对电能质量进行多角度分析.该研究通过对电能质量特征进行量化分析,及时获取谐波、间...     

Power system harmonic signal estimation and retrieval for activepower filter applications

This paper presents a new adaptive infinite impulse response (IIR) line enhancer (LE) comb filter configuration for the purpose of power system harmonic signal estimation and retrieval. The approximate maximum likelihood (AML) algorithm is employed for the parameter update. The proposed solution is characterised by modest computational burden, effective tracking capabilities and provides the retrieved harmonic components with little or no distortion. The retrieved power system harmonics may be obtained on an individual basis or as a composite signal. Practical test results are included which show the performance achieved by the proposed technique     

A hybrid approach to harmonic retrieval in non-Gaussian ARMA noise

Addresses the harmonic retrieval problem in colored noise. As contrasted to the reported studies in which Gaussian noise was assumed, this paper focuses on additive non-Gaussian ARMA noise. Our approach is hybrid in the sense that third-order cumulants are first used to identify the AR part of the non-Gaussian noise process, and then correlation-based high-resolution methods are used for the filtered process to estimate the number of harmonics and their frequencies. Simulation examples are presented to demonstrate the high resolution of this approach     

Computational analysis of rotational search methods for adaptivePisarenko harmonic retrieval

The rotational search method (RSM), which reduces the computational burden of the Pisarenko method for identifying undamped sinusoids in additive noise, is discussed. A brief review of previous adaptive algorithms for implementing the method is presented. Two simulations are presented which show the inherent sensitivity of the RSM algorithm. The sensitivity is shown to depend upon the Rayleigh-Ritz eigenvector estimate and the value of the minimum eigenvalue estimate. The errors in their tracking result in a loss of search direction orthogonality to the estimated minimum eigenvector. A higher precision for the enforced search direction orthogonality which minimizes the added computation is proposed, resulting in the altered RSM (ARSM)     

Improvements of a state-space iterative noise reduction algorithmfor harmonic retrieval

When the model of a noisy sinusoidal process is autoregressive moving average (ARMA), then the AR spectrum is biased. However, since the AR spectrum contains all the second-order information of the process, it is possible to retrieve the noiseless predictor from the noisy one. An iterative algorithm enabling the computation of the ARMA parameters from the AR parameters and a new well-suited initialization scheme are presented. Simulations of the state-space iterative noise reduction algorithm (SINA) are performed using various AR estimators. The mean-square-error graph is plotted for all these estimators and performances of the methods are discussed     

基于特征距离与极谐变换的图像检索算法

为提高图像在数据集中的检索准确度,设计了基于加权距离与多元极谐变换的图像检索算法。在查询图像的色调－饱和度－亮度(HSV)空间内,提取其颜色特征;并引入贝塞尔K分布与非下采样Shearlet变换(NSST)方法得到查询图像的纹理特征,改善其对模糊与亮度变换等操作的稳健性;借助四元极谐变换(QPHT)机制,将图像的QPHT模系数视为形状特征,提高对噪声与几何变换的鲁棒性。通过融合这3种特征,分别计算查询图像与数据库图像之间对应的特征距离,并赋予三者对应的权重,以测量两幅图像之间的相似度,从而准确输出检索结果。测试数据显示,与当前基于内容的图像检索技术相比,所提算法具备更高的检索准确度和鲁棒性,在多种几何变换攻击下,仍可以准确检索出目标。     

Development and analysis of a neural network approach toPisarenko's harmonic retrieval method

Pisarenko's harmonic retrieval (PHR) method is perhaps the first eigenstructure based spectral estimation technique. The basic step in this method is the computation of eigenvector corresponding to the minimum eigenvalue of the autocorrelation matrix of the underlying data. The authors recast a known constrained minimization formulation for obtaining this eigenvector into the neural network (NN) framework. Using the penalty function approach, they develop an appropriate energy function for the NN. This NN is of feedback type with the neurons having sigmoidal activation function. Analysis of the proposed approach shows that the required eigenvector is a minimizer (with a given norm) of this energy function. Further, all its minimizers are global minimizers. Bounds on the integration time step that is required to numerically solve the system of nonlinear differential equations, which define the network dynamics, have been derived. Results of computer simulations are presented to support their analysis     

Two-dimensional transverse-magnetic time-domain scattering using the Nystro/spl uml/m method and bandlimited extrapolation

A method is presented for the solution of the integral equations that describe the electromagnetic scattering from an infinitely long conducting cylinder in the time domain. The method discretizes the integral equations spatially using a high-order locally-corrected Nystro/spl uml/m method and temporally using a filtered kernel. The filtering of the kernel both controls aliasing and reduces the order of its singularity. On the other hand, filtering also gives rise to a noncausal kernel so the time marching is accomplished with a bandlimited extrapolation scheme. Numerical results demonstrate the stability and accuracy of the proposed method.     

Simple test for distinguishing constant from time-varying amplitudein harmonic retrieval problems

In many harmonic retrieval problems, it is not known a priori whether the amplitude of the sinusoidal signals dealt with is constant or time varying. In such applications, a key problem, prior to or in conjunction with frequency estimation, is to decide between these two alternatives or hypotheses. A statistical test for this problem is derived, based on the statistics of the difference between two frequency estimates. The test is computationally efficient and yields, as a by-product, consistent frequency estimates under either hypothesis. Numerical examples are included to show the performance of the proposed test     

Nonlinear filtering methods for harmonic retrieval and model orderselection in Gaussian and non-Gaussian noise

This paper addresses the problem of high-resolution parameter estimation (harmonic retrieval) and model-order selection for superimposed sinusoids. The harmonic retrieval problem is analyzed using a nonlinear parameter estimation approach. Estimation is performed using several nonlinear estimators with signals embedded in white and colored Gaussian noise. Simulation results demonstrate that the nonlinear filters perform close to the Cramer-Rao bound. Model order selection is performed in Gaussian and non-Gaussian noise. The problem is formulated using a multiple hypothesis testing approach with assumed known a priori probabilities for each hypothesis. Parameter estimation is performed using the extended Kalman filter when the noise is Gaussian. The extended high-order filter (EHOF) is implemented in non-Gaussian noise. Simulation results demonstrate excellent performance in selecting the correct model order and estimating the signal parameters     

Ultrafast time-domain technology and its application in all-optical signal processing

In this paper, we review recent advances in ultrafast optical time-domain technology with emphasis on the use in optical packet switching. In this respect, several key building blocks, including high-rate laser sources applicable to any time-division-multiplexing (TDM) application, optical logic circuits for bitwise processing, and clock-recovery circuits for timing synchronization with both synchronous and asynchronous data traffic, are described in detail. The circuits take advantage of the ultrafast nonlinear transfer function of semiconductor-based devices to operate successfully at rates beyond 10 Gb/s. We also demonstrate two more complex circuits-a header extraction unit and an exchange-bypass switch-operating at 10 Gb/s. These two units are key blocks for any general-purpose packet routing/switching application. Finally, we discuss the system perspective of all these modules and propose their possible incorporation in a packet switch architecture to provide low-level but high-speed functionalities. The goal is to perform as many operations as possible in the optical domain to increase node throughput and to alleviate the network from unwanted and expensive optical-electrical-optical conversions.