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learning a Locality Preserving subspace for ISAR Target Recognition

Learning a Locality Preserving subspace for ISAR Target Reco...

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2nd international conference on Information and Computing Science

作者： Cai, Hong He, Qiang Han, Zhuang-Zhi Shang, Chao-Xuan Ordnance Engn Coll Dept Opt & Elect Engn Shijiazhuang Peoples R China

ISBN: (纸本)9780769536347

Io order to overcome the instability of Inverse synthetic aperture radar (ISAR) image caused by shift, rotation and scale variation, a new approach based on Locality Preserving Projections (LPP) algorithm of manifold learning is proposed to feature analysis in ISAR target recognition. Firstly, the LPP algorithm is used to reduce the dimensionality of the ISAR image, and then the reduced feature is classified by k-nearest neighbor classification with rejection recognition capability. Experimental results on four kinds of aircraft target suggest that the LPP algorithm has the capability of finding the low-dimensional manifold structure embedded in the high-dimensional ISAR image space, which is controlled by few parameters, such as attitude angle, scale and position, etc., and the better classification performance is acquired with the low-dimensional feature.

关键词： manifold learning locality preserving projections ISAR image target recognition

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ASSESSMENT And COMPARISON OF TIME REALIGNMENT METHODS FOR SUPERVISED HEART BEAT CLASSIFICATION

ASSESSMENT AND COMPARISON OF TIME REALIGNMENT METHODS FOR SU...

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2nd international conference on Bio-Inspired Systems and signal processing

作者： de Lannoy, G. Verleysen, M. Delbeke, J. Catholic Univ Louvain Machine Learning Grp Pl Levant 3 B-1348 Louvain La Neuve Belgium Catholic Univ Louvain Dept Physiol & Pharmacol B-1200 Brussels Belgium

ISBN: (纸本)9789898111654

A reliable diagnosis of cardiac diseases can sometimes only be obtained by observing the heart of a patient for a long time period where every single heart beat is of importance. Computer-aided classification of heart beats is therefore of great help. The classification of the complete heart beat has many advantages compared to a classification of the QRS complex only or feature extraction methods. Nevertheless, the task is challenging because of the time-varying property of the heart beats. In this work, four time-alignment methods are evaluated and compared in the context of supervised heart beat classification. Among the four methods are three time series resampling methods by linear interpolation, cubic splines interpolation and trace segmentation. The fourth method is a realignment algorithm by dynamic time warping. The multiple sources of artifacts are filtered by discrete wavelet transform. As it only relies on a dissimilarity measure, the k-nearest neighbor classifier is a suitable choice for supervised classification of time series like ECG signals in multiple classes. Two different experiments corresponding to inter-patient and intra-patient classification are conducted on representative dataset built from the standard public MIT-BIH arrhythmia database.

关键词： Heart beat classification Time realignment Dynamic time warping Trace segmentation Wavelet transform Nearest neighbor classifier

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Phonetic classification with spiking neural network using a gradient descent rule

Phonetic classification with spiking neural network using a ...

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2nd international conference on Computer and Electrical Engineering

作者： Ourdighi, A. Lacheheb, S. E. Benyettou, A. Mohamed Boudiaf Sci & Technol Univ Fac Sci Dept Comp Sci Signal Image Speech Lab SIMPA Oran Algeria

ISBN: (纸本)9780769539256

Being the closest model of the biological neuron, the spiking neuron is the third and newest generation of artificial neuron. the particularity of this neuron is the use of temporal coding to pass information between network units. Using such codes allows the transmission of a large amount of data with only few spikes, simply one or zero for each neuron involved in the specific processing task. the true deal is how to encode analogical information to a spikes train. More, it's not the only problem which we find in using spiking neurons network (SNN), we have to choose different parameters and functions. In this paper, in the middle of several spiking neurons models, we have chosen the spiking response model (SRM) to apply in phonetic classification using phonemes from TIMIT databases. Before, for the studies, we have performed experiments for the classical Xor-problem and explore the impact of encoding information on the network structure. The learning rules used in this experiment was based on error backpropagation based on time to first spike.

关键词： SNN Spike Integrate and fire time to first spike

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Evaluation on competitiveness of TPL enterprises based on AHP & genetic algorithm

Evaluation on competitiveness of TPL enterprises based on AH...

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international conference on Computer Science and Information Technology (CSIT)

作者： Yan Ge School of Business Administration Shandong University of Finance Ji'nan 250014 China

Third party logistics is the advanced form of modern logistics for socialization and specialization. The evaluation optical selection of third-party logistics enterprises increasingly becomes the key points of the recycling economy and green environmental protection industry. Analytical hierarchy process (AHP), a commonly used quantitative research method, is the widely used evaluation indicator solution. The genetic algorithm which is one of the major technologies of intelligent calculation, with adaptively dynamic adjustment and global optimization capability, has been widely used in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life. Based on the characteristics of the two methods, the paper designs a program making real-time feedback of information according to AHP, adopting genetic algorithm combined with AHP dynamic adjusting third party logistics enterprises competitiveness evaluation index weights, to further enhance the objectivity and efficiency of the system evaluation of third party logistics enterprises.

关键词： Genetic algorithms Logistics Optical feedback Optical signal processing Recycling Protection Artificial intelligence learning systems machine learning signal processing algorithms

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Integrative learning in Engineering Education by Action Research Method

Integrative Learning in Engineering Education by Action Rese...

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2nd international Multi-conference on Society, Cybernetics and Informatics

作者： Pendharkar, Gita Judge, Sukhvir Gredeskoul, Olga RMIT Univ SIEBS Melbourne Vic 3170 Australia

ISBN: (纸本)9781934272473

Demanding industry standards and rapidly changing technology creates a lot of challenge for graduate engineers in terms of engineering knowledge. A graduate engineer needs to be confident in testing real life systems. However, in general, it is observed that the students lack practical skills and find it hard to integrate two or more courses in the program. By using action research in teaching and learning, the potential of applying integrative learning to engineering curricula is researched. The aim in this paper is to enhance integrative learning by introducing a common project for two different courses, Digital signal processing which is a theoretical course and Microprocessor Applications which is a practical oriented course.

关键词： Engineering education

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A Dynamical System for Online learning of Periodic Movements of Unknown Waveform and Frequency

A Dynamical System for Online Learning of Periodic Movements...

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2nd Biennial IEEE RAS-EMBS international conference on Biomedical Robotics and Biomechatronics (BioRob 2008)

作者： Gams, Andrej Righetti, Ludovic Ijspeert, Auke Jan Lenarcic, Jadran IJS Jamova Cesta 39 Ljubljana 1000 Slovenia Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland

ISBN: (纸本)9781424428823

The paper presents a two-layered system for learning and encoding a periodic signal onto a limit cycle without any knowledge on the waveform and the frequency of the signal, and without any signal processing. The first dynamical system is responsible for extracting the main frequency of the input signal. It is based on adaptive frequency phase oscillators in a feedback structure, enabling us to extract separate frequency components without any signal processing, as all of the processing is embedded in the dynamics of the system itself. The second dynamical system is responsible for learning of the waveform. It has a built-in learning algorithm based on locally weighted regression, which adjusts the weights according to the amplitude of the input signal. By combining the output of the first system with the input of the second system we can rapidly teach new trajectories to robots. The systems works online for any periodic signal and can be applied in parallel to multiple dimensions. Furthermore, it can adapt to changes in frequency and shape, e.g. to non-stationary signals, and is computationally inexpensive. Results using simulated and hand-generated input signals, along with applying the algorithm to a HOAP-2 humanoid robot are presented.

关键词： Dynamical systems

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Electronic implementation of biologically inspired neuromorphic vision sensor

Electronic implementation of biologically inspired neuromorp...

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2nd Asia international conference on Modelling and Simulation, AMS 2008

作者： Gangwar, D.S. Tiwari, Tarun Singh, Baldev Department of ECE GLAITM Mathura 17th Km. Stone NH-2 Mathura India

ISBN: (纸本)9780769531366

Neuromophic vision sensor is an electronic implementation of vision algorithm on semiconductor. Neuromophic systems are biologically inspired artificial neural systems that mimic algorithmic behavior of biological systems. The focus of this paper is to highlight photo transduction operation and conversion of optical information into the neuronal signal in the similar fashion as it takes place in biological retina. These systems have efficient adaptive and intelligent control techniques resembling with biological nervous system based on optical and electronic signal processing properties of semiconductor materials. Proposed electronic model contains adaptive photoreceptors as light sensors and other circuit components such as averaging circuits;circuits representing ganglion cells;neuronal firing circuits etc these entire elements junction to sense brightness, size, shape and orientation to distinguish objects in closer proximity. Neuromophic vision chip can lead towards development of sensory based artificial systems having parallel collective computation, adaptation, learning and memory implemented locally at each stage of processing of information. © 2008 IEEE.

关键词： Semiconductor materials

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Reduced set support vector machines: Application for 2-dimensional datasets

Reduced set support vector machines: Application for 2-dimen...

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international conference on signal processing and Communication Systems, ICSPCS

作者： A. Hussain S. Shahbudin H. Husain S. A. Samad N. Md Tahir Electrical Electronics & System Engineering Department Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Selangor Darul Ehsan Malaysia Faculty of Electrical Engineering Universiti Teknologi Mara Shah Alam Selangor Darul Ehsan Malaysia

This paper presents the performance of the reduced set (RS) method to approximate the decision boundary for standard support vector machines (SVM) classifier without affecting its generalization performance. The main focus of this work is to demonstrate the capability of the RS method such that even with fewer set of vectors, the generalization performance is not affected. In evaluating the RS method performance, decision boundaries obtained using RS method were benchmarked against the decision boundaries obtained from the standard SVM using sequential minimal optimization (SMO) method. Specifically, the generalization ability of the two methods is not evaluated since the main objective is to analyze the effect of reduced set vector in producing approximation of SVM decision rules. Results obtained demonstrated that the SVM classifier using RS method is comparable with the standard SVM using SMO method. In fact, the RS method is better since it uses fewer set of vectors to produce similar decision boundaries while maintaining the generalization performances.

关键词： Support vector machines Support vector machine classification Data visualization Systems engineering and theory Optimization methods Performance analysis Standards development machine learning algorithms Pattern analysis Humans

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Development of artificial-intelligent power quality diagnosis equipment for single-phase power system

Development of artificial-intelligent power quality diagnosi...

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National proceedings Power and Energy conference (PECon)

作者： Sun-Geun Kwack Gyo-Bum Chung Jaeho Choi Ginkyu Choi Department of Electronic & Electrical Eng. Hongik University Jochiwon Chungnam South Korea School of Electrical and Computer Eng. Chungbuk National University Chungbuk South Korea

A DSP process-based equipment to diagnose the power quality of a single-phase power system is developed. The artificial-intelligent equipment diagnoses the transient, the voltage sag, the voltage swell and the THD among the power quality index of a power system. The 256 data sampled in a period of the single-phase voltage of the power system are used for the real-time calculation of RMS value, Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT). The type of mother function for DWT is DB4. The data are measured at 154kV or 22.9kV substations for a year. The feature vectors extracted from the data are used to train the neural network for the artificial-intelligent diagnosis of power quality. The type of the activation function in the neural network is sigmoidal. After learning with the feature vectors, the back-propagation algorithm simulated in PSIM program and C ++ code generates the weights and biases of the neural network, which are used in the DSP320C6713-based Artificial-Intelligent Power Quality Diagnosis Equipment (AIPQDE). The developed equipment detects satisfactorily the PQ problems in a real situation simulated in the laboratory.

关键词： Power quality Power systems Power system transients Discrete wavelet transforms Voltage fluctuations Artificial neural networks Power system measurements Fast Fourier transforms Digital signal processing Real time systems

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Comparison of background subtraction methods for a multimedia learning space

Comparison of background subtraction methods for a multimedi...

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2nd international conference on signal processing and Multimedia Applications

作者： El Baf, F. Bouwmans, T. Vachon, B. Univ La Rochelle Lab LMA Ave M Crepeau La Rochelle France

ISBN: (纸本)9789898111135

This article presents, at a first time, a multimedia application called Aqu@theque. This project consists in elaborating a multimedia system dedicated to aquariums which gives ludo-pedagogical information in an interactive learning area. The reliability of this application depends of the segmentation and recognition steps. Then, we focus on the segmentation step using the background subtraction principle. Our motivation is to compare different background subtraction methods used to detect fishes in video sequences and to improve the performance of this application. In this context, we present a new classification of the critical situations which occurred in videos and disturbed the assumptions made in background subtraction methods. This classification can be used in any application using background subtraction like video surveillance, motion capture or video games.

关键词： multimedia application video processing background subtraction

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