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Optimal approximation of linear systems by artificial immune response

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Science in China(Series F) 2006年第1期49卷 63-79页

作者： GONG Maoguo DU Haifeng JIAO Licheng Institute of Intelligent Information processing and Key laboratory of radar signal processing Xidian University Xi'an 710071 China School of Mechanical Engineering Xi'an Jiaotong University Xi'an 710049 China

This paper puts forward a novel artificial immune response algorithm for optimal approximation of linear systems. A quaternion model of artificial immune response is proposed for engineering computing. The model abstracts four elements, namely, antigen, antibody, reaction rules among antibodies, and driving algorithm describing how the rules are applied to antibodies, to simulate the process of immune response. Some reaction rules including clonal selection rules, immunological memory rules and immune regulation rules are introduced. Using the theorem of Markov chain, it is proofed that the new model is convergent. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new model have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm and the multi-agent genetic algorithm.

关键词： approximation of linear systems artificial immune systems immune response clonal selection,immunological memory

Co-Sharing Waveform Design for Millimeter-Wave radar Communication Systems

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China Communications 2024年第6期21卷 305-318页

作者： Cui Gaofeng He Mengmin Xu Lexi Wang Changheng Wang Weidong School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Key laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China China United Network Communications Corporation Beijing 100048China

Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless ***,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication *** this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing *** eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given *** results show that the bit error rate(BER)of CSW is close to that of the pure communication ***,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.

关键词： co-sharing waveform millimeter-wave radar communication radar sensing range and velocity estimation

Generalized system function analysis of resonant behavior of electromagnetic open systems

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Science in China(Series F) 2005年第5期48卷 615-631页

作者： LI Long LIU Haixia SHI Yan LIANG Changhong national laboratory of Antennas and Microwave Technology Xidian University Xi'an 710071 China Institute of signal and Data processing Xidian University Xi'an 710071 China

Abstract The generalized system function, H（s）, directly associated with the radiated or scattered fields is presented to effectively analyze the special resonant behavior of electromagnetic open systems in this paper, which is adaptively constructed by using the model-based parameter estimation （MBPE） technique in the complex frequency domain. By analyzing the characteristics of complex zeros, poles and residues of H（s） in a finite operational frequency band, we can effectively determine resonant frequencies and resonant intensity of electromagnetic open systems. It is known that an analysis of Q-factor of antenna and scattering systems has been an interesting and challenging problem. Based on H（s） and the complex frequency w theories, a complex frequency method for Q-factor of electromagnetic open systems is presented in this paper. Some examples of the practical antenna arrays are given to illustrate the applications and validity of the generalized system function theory proposed by this paper.

关键词： Keywords: generalized system function H(s) electromagnetic open resonance complex frequency qualityfactor Q model-based parameter estimation (MBPE)

Volterra Feedforward Neural Networks:Theory and Algorithms

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Journal of Systems Engineering and Electronics 1996年第4期7卷 1-12页

作者： Jiao Lichengl Liu Fang & Xie Qin(national Lab. for radar signal processing and Center for Neural Networks,xidian university, Xian 710071, P.R.China) national Lab. for radar signal processing and Center for Neural Networks Xidian University Xian 710071 P.R. China

The Volterra feedforward neural network with nonlinear interconnections and related homotopy learning algorithm are proposed in the paper. It is shown that Volterra neural network and the homolopy learning algorithms are significant potentials in nonlinear approximation ability,convergent speeds and global optimization than the classical neural networks and the standard BP algorithm, and related computer simulations and theoretical analysis are given too.

关键词： Volterra neural networks Homotopy learning algorithm.

Blind source separation with unknown and dynamically changing number of source signals

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Science in China(Series F) 2006年第5期49卷 627-638页

作者： YE Jimin ZHANG Xianda ZHU Xiaolong Key laboratory for radar signal processing Xidian University Xi'an 710071 China Department of Automation State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China

The contrast function remains to be an open problem in blind source separation （BSS） when the number of source signals is unknown and/or dynamically changed. The paper studies this problem and proves that the mutual information is still the contrast function for BSS if the mixing matrix is of full column rank. The mutual information reaches its minimum at the separation points, where the random outputs of the BSS system are the scaled and permuted source signals, while the others are zero outputs. Using the property that the transpose of the mixing matrix and a matrix composed by m observed signals have the indentical null space with probability one, a practical method, which can detect the unknown number of source signals n, ulteriorly traces the dynamical change of the sources number with a few of data, is proposed. The effectiveness of the proposed theorey and the developed novel algorithm is verified by adaptive BSS simulations with unknown and dynamically changing number of source signals.

关键词： blind source separation independent component analysis natural gradient mutual information contrast function neural networks.

Highly robust ground moving target detection and relocation method for distributed satellites

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Frontiers of Electrical and Electronic Engineering in China 2008年第4期3卷 425-434页

作者： Ying LIU Guisheng LIAO Zhengguang ZHOU national laboratory of radar signal processing Xidian UniversityXi’an 710071China Nanjing Research Institute of Electronics Technology Nanjing 210013China

The performance of ground moving target detection for distributed satellites will be affected signifi-cantly when there is an image registration error,clutter decorrelation and array *** this paper,a new approach to moving target detection and relocation is proposed based on multi-channel and multi-pixel adap-tive signal processing in an image ***,multi-channel and multi-pixel joint data are equated to a simple array *** that there is an image registration error,the real steering vector of the moving target can be estimated through a space projection *** optimal beam forming approach is used to cancel clutter,and at the same time the cross-track velocity of the mov-ing target can be determined by searching for the peak value of the cost *** moving target can then be relocated on the SAR *** simulation results indicate that this method has a good robustness to image registration error,clutter decorrelation and array *** detection performance and the estimation accuracy are significantly improved.

关键词： distributed satellite ground moving target detection cost function image registration error optimal beam forming

Fast adaptive principal component extraction based on a generalized energy function

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Science in China(Series F) 2003年第4期46卷 250-261页

作者：欧阳缮保铮廖桂生 national Key laboratory of radar signal processing Xidian University Xi'an 710071 China Department of Communication and Information Engineering Guilin University of Electronic Technology Guilin 541004 China

By introducing an arbitrary diagonal matrix, a generalized energy function (GEF) is proposed for searching for the optimum weights of a two layer linear neural network. From the GEF, we derive a recur- sive least squares (RLS) algorithm to extract in parallel multiple principal components of the input covari- ance matrix without designing an asymmetrical circuit. The local stability of the GEF algorithm at the equilibrium is analytically verified. Simulation results show that the GEF algorithm for parallel multiple principal components extraction exhibits the fast convergence and has the improved robustness resis- tance to the eigenvalue spread of the input covariance matrix as compared to the well-known lateral inhi- bition model (APEX) and least mean square error reconstruction (LMSER) algorithms.

关键词： linear neural networks principal component analysis generalized energy function recursive least squares (RLS) algorithm stability analysis.

Grading learning for blind source separation

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Science in China(Series F) 2003年第1期46卷 31-44页

作者：张贤达朱孝龙保铮 Key laboratory for radar signal processing Xidian University Department of Automation State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China

By generalizing the learning rate parameter to a learning rate matrix, this paper proposes a grading learning algorithm for blind source separation. The whole learning process is divided into three stages: initial stage, capturing stage and tracking stage. In different stages, different learning rates are used for each output component, which is determined by its dependency on other output components. It is shown that the grading learning algorithm is equivariant and can keep the separating matrix from becoming singular. Simulations show that the proposed algorithm can achieve faster convergence, better steady-state performance and higher numerical robustness, as compared with the existing algorithms using fixed, time-descending and adaptive learning rates.

关键词： blind source separation independent component analysis neural computation adaptive learning.

radar HRRP RECOGNITION BASED ON THE MINIMUM KULLBACK-LEIBLER DISTANCE CRITERION

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Journal of Electronics(China) 2007年第2期24卷 199-203页

作者： Yuan Li Liu Hongwei Bao Zheng Key Lab for radar signal processing Xidian University Xi＇an 710071 China

To relax the target aspect sensitivity and use more statistical information of the High Range Resolution Profiles (HRRPs), in this paper, the average range profile and the variance range profile are extracted together as the feature vectors for both training data and test data representa-tion. And a decision rule is established for Automatic Target Recognition (ATR) based on the mini-mum Kullback-Leibler Distance (KLD) criterion. The recognition performance of the proposed method is comparable with that of Adaptive Gaussian Classifier (AGC) with multiple test HRRPs, but the proposed method is much more computational efficient. Experimental results based on the measured data show that the minimum KLD classifier is effective.

关键词：雷达高距离分辨象自动目标识别自适应高斯分类器 KULLBACK-LEIBLER距离标准