小波包分析在故障特征提取与识别中的应用

对观测信号进行小波包分析,从而提取故障信息,建立能够表征系统特征的状态向量,用模式识别的方法对系统进行故障检测与定位,实现系统的故障诊断。     

一种新的Morlet小波及其在雷达信号特征提取中的应用研究

为准确估计雷达信号的瞬时频率,文中提出了一种基于新Morlet小波原子提取信号小波脊线的方法。通过分析小波脊线原理,使用新Morlet小波原子提取雷达辐射源信号的小波脊线特征。同时,针对不同调制类型的雷达信号,根据小波分解时—频约束关系,分析了正确提取信号脊线特征的条件。仿真实验表明,与普通Morlet小波原子相比,基于改进的Morlet小波提取信号脊线特征具有较强的检测概率和抗噪性能,其方法的有效性为实验结果所证实。     

Generation of CW MMW using optical signal propagating nonlinear materials for wireless communications and ubiquitous communications systems

A continuous-wave (CW) millimetre-wave (MMW) was generated by using optical signal propagating nonlinear materials for MMW wireless communications and ubiquitous communications systems. The generated MMW signals were radiated in a millimetre waveguide and detected by a detector. The spectral linewidth of the MMW signals was less than 1 kHz, and the power fluctuation of the MMW was less than 1.5 dB over a 30-50 GHz range.     

语音信号中的情感特征分析和识别的研究

本文分析了含有欢快、愤怒、惊奇、悲伤等４种情感语音信号的时间构造、振幅构造、基频构造和共振峰构造的特征。通过和不带情感的平静语音信号的比较,总结了不同情感语音信号的情感特征的分布规律。根据这些分析,提取了９个情感特征进行了情感识别的实验,获得了基本上接近于人的正常表现的识别结果。     

Color image canonical correlation analysis for face feature extraction and recognition

Canonical correlation analysis (CCA) is a powerful statistical analysis technique, which can extract canonical correlated features from two data sets. However, it cannot be directly used for color images that are usually represented by three data sets, i.e., red, green and blue components. Current multi-set CCA (mCCA) methods, on the other hand, can only provide the iterative solutions, not the analytical solutions, when processing multiple data sets. In this paper, we develop the CCA technique and propose a color image CCA (CICCA) approach, which can extract canonical correlated features from three color components and provide the analytical solution. We show the mathematical model of CICCA, prove that CICCA can be cast as solving three eigen-equations, and present the realization algorithm of CICCA. Experimental results on the AR and FRGC-2 public color face image databases demonstrate that CICCA outperforms several representative color face recognition methods.     

A suboptimal receiver for joint spatial-temporal filtering andmultiuser detection in mobile radio communications

This paper proposes a suboptimal receiver for joint spatial-temporal filtering and multiuser detection in mobile radio communications using single carrier signaling. The proposed receiver is a reasonable approximation of the maximum likelihood (ML) based optimal receiver described in the present paper. A cascaded connection of an adaptive array antenna and an ML multiuser sequence estimator is the basis of the proposed receiver. The major advantages of the proposed receiver over conventional adaptive array antennas are: (1) delayed path components of desired signals can be effectively combined; (2) interference signals exceeding the degree of freedom; and (3) those having the same incident angle as that of desired path components can both be suppressed. The proposed receiver does not require prohibitively large computational complexity. Results of computer simulations presented in this paper show that the proposed receiver exhibits excellent performance even in severe multipath fading environments     

频率方向图复合可重构寄生单极子天线阵列

提出了一种能应用于无线通讯系统的新型介质支撑开关寄生阵列天线。基于八木天线原理,天线可以实现频率及方向图的复合可重构。所引入的开关用来切换不同状态的工作频率并实现方向图的扫描。地支结构用来改善天线的阻抗匹配并展宽频带。测量结果表明：天线阵列可以在保证回波损耗小于-10 dB的情况下完全覆盖1710~1880 MHz、1850~1990 MHz及2400~2480 MHz三个移动通信频段,并可以方便地实现频率切换及方向图扫描。     

一种基于小波变换的文字检测与提取方法

视频中包含的文字信息与视频的语义内容有很强的相关性,将视频中的文字信息提取出来进行分析处理可以有效地理解电视视频语义,从而实现对视频内容的安全监控。针对文字检测提出一种基于小波变换、角点特征图像和统计特征的有效方法,并运用基于彩色空间的文字提取方法获取二值图像,更有利于后面OCR的文字识别。     

Statistical model and local binary pattern based texture feature extraction in dual-tree complex wavelet transform domain

This paper presents a new feature extraction method in dual-tree complex wavelet transform domain. Given an input image, we obtain all highpass directional subimages and a set of pyramid lowpass subimages with different resolutions by applying DTCWT decomposition. After that, generalized Gamma density \((\hbox {G}\Gamma \hbox {D})\) models and local binary pattern are utilized respectively to characterize features of both highpass and lowpass subimages. The two kinds of features are combined for texture classification, and the experimental results on datasets Brodatz, Outex and UMD demonstrate that our proposed method can achieve superior classification accuracy than other state-of-the-art methods.     

Advances in signal processing for wireless and wired communications [Guest Editorial]

The six articles in this feature topic cover advances in signal processing for wireless and wired communications.     

语音信号的情感特征分析与识别研究综述

语音情感的分析与识别是近年来新兴研究课题之一，本文介绍了近几年来国内外语音情感识别的状况，阐述了各种人类情感分类的方法，归纳了各种语音特征参数的提取方法以及各特征参数对情感识别的意义，在此基础上综述了国内外在情感识别领域的研究进展与主要识别建模方法，同时总结了各种识别建模方法的利弊。最后概括了语音情感识别领域的发展趋势，并进行了展望。     

A hybrid feature extraction and machine learning approaches for epileptic seizure detection

Multidimensional Systems and Signal Processing - Epileptic seizure detection from the brain EEG signals is an essential step for speeding up the diagnosis that assists researchers and medical...     

A multielement array antenna with additional constraints on the radiation pattern for operation in wireless communications systems

An algorithm for neutralization of the multipath-propagation effect with substantial angular spread is proposed. This algorithm is more stable than similar classical algorithms. Additional stability is attained owing to the use of artificial constraints that allow formation of wide nulls in the direction of interferences and wide maxima in the direction of the desired signal. The null width can be changed via selection of the order of the imposed constraints. The complexity of the hardware implementation of such a system can be decreased because requirements for the accuracy of estimated values of angular coordinates become less stringent.     

Error control for multimedia communications in wireless sensor networks: A comparative performance analysis

The emerging multimedia applications of Wireless Sensor Network (WSNs) impose new challenges in design of algorithms and communication protocols for such networks. In the view of these challenges, error control is an important mechanism that enables us to provide robust multimedia communication and maintain Quality of Service (QoS). Despite the existence of some good research works on error control analysis in WSNs, none of them provides a thorough study of error control schemes for multimedia delivery. In this paper, a comprehensive performance evaluation of Automatic Repeat Request (ARQ), Forward Error Correction (FEC), Erasure Coding (EC), link-layer hybrid FEC/ARQ, and cross-layer hybrid error control schemes over Wireless Multimedia Sensor Network (WMSNs) is performed. Performance metrics such as energy efficiency, frame Peak Signal-to-Noise Ratio (PSNR), frame loss rate, cumulative jitter, and delay-constrained PSNR are investigated. The results of our analysis show how wireless channel errors can affect the performance of multimedia sensor networks and how different error control scenarios can be effective for those networks. The results also provide the required insights for efficient design of error control protocols in multimedia communications over WSNs.     

A new eigenstructure method for sinusoidal signal retrieval inwhite noise: estimation and pattern recognition

A new approach, in a framework of an eigenstructure method using a Hankel matrix, is developed for sinusoidal signal retrieval in white noise. A closed-form solution for the singular pairs of the matrix is defined in terms of the associated sinusoidal signals and noise. The estimated sinusoidal singular vectors are applied to form the noise-free Hankel matrix. A pattern recognition technique is proposed for partitioning signal and noise subspaces based on the singular pairs of the Hankel matrix. Three types of cluster structures in an eigen-spectrum plot are identified: well-separated, touching, and overlapping. The overlapping, which is the most difficult case, corresponds to a low signal-to noise ratio (SNR). Optimization of Hankel matrix dimensions is suggested for enhancing separability of cluster structures. Once features have been extracted from both singular value and singular vector data, a fuzzy classifier is used to identify each singular component. Computer simulations have shown that the method is effective for the case of “touching” data and provides reasonably good results for a sinusoidal signal reconstruction in the time domain. The limitations of the method are also discussed     

A novel wavelet transform-based transient current analysis for fault detection and localization

Transient current (IDD) testing has been often cited and investigated as an alternative and/or supplement to quiescent current (IDDQ) testing. In this correspondence, we present a novel integrated method for fault detection and localization using wavelet transform-based IDD waveform analysis. The time-frequency resolution property of wavelet transform helps us detect as well as localize faults in digital CMOS circuits. Experiments performed on measured data from a fabricated 8-bit shift register, and simulation data from more complex circuits show promising results for both detection and localization. Wavelet-based detection method shows better sensitivity than spectral and time-domain methods. Effectiveness of the localization method in presence of complex power supply network, measurement noise, and process variation is also addressed.     

Application of wavelet analysis and artificial neural networks in solving the problem concerning shape recognition of noisy pulsed signals

The problem concerning recognition of single pulses under the action of interferences is discussed by the example of classification of neuron action potentials. Joint applications of wavelets and artificial neural networks in solving the the given problem are analyzed. The recognition method, which is based on wavelet neural networks and ensures adjustment of the synapses of a supplementary (??wavelet??) layer, has been proposed. It is demonstrated that experimental data can efficiently be analyzed via the proposed method.     

A theoretical analysis of the performance of code division multipleaccess communications over multimode optical fiber channels-part I:transmission and detection

This paper presents results of a theoretical investigation to evaluate the performance of code division multiple access communications over multimode optical fiber channels in an asynchronous, multiuser communication network environment. The system is evaluated using Gold sequences for spectral spreading of the baseband signal from each user employing direct-sequence biphase shift keying and intensity modulation techniques. The transmission channel model employed is a lossless linear system approximation of the field transfer function for the α-profile multimode optical fiber. Due to channel model complexity, a correlation receiver model employing a suboptimal receive filter was used in calculating the peak output signal at the ith receiver. The performance measures for the system, i.e., signal-to-noise ratio and bit error probability for the ith receiver, are derived as functions of channel characteristics, spectral spreading, number of active users, and the hit energy to noise (white) spectral density ratio