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2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009

作者： Wu, Chao-Cheng Chang, Chein-I. Ren, Husen Chang, Yang Lang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Center for Space and Remote Sensing Research National Central University Jhong-Li Tao-Yuan Taiwan Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9781424433957

Simplex growing algorithm (SGA) was recently developed as an alternative to the N-finder algorithm (N-FINDR) which is shown to be a promising endmember extraction technique. This paper further extends the SGA to a real-time processing algorithm, referred to as real-time SGA (RT SGA) that can effectively address four major issues arising in practical implementation for N-FINDR, (1) use of random initial endmembers which causes inconsistent final results, (2) very high computational complexity which results from an exhaustive search for finding all endmembers simultaneously, (3) requirement of dimensionality reduction because of enormous data volumes to be processed and (4) lack of real-time capability. ©2009 IEEE.

关键词： Extraction

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A theoretical model for spontaneous seizure generation based on Markov chain process

A theoretical model for spontaneous seizure generation based...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： Farzaneh Shayegh Saeed Sadri Rasoul AmirFattahi Digital signal Processing Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

Here a theoretical model for seizure generation is presented. This is done according to a simple physiological model of epileptic activities in which seizure occurrence is mainly attributed to imbalance of excitatory/inhibitory ratio. Although factors that play a role in ictogenesis are not exactly known, this process can be assumed as a stochastic process. Indeed, we claim that in neural synapses both excitatory and inhibitory gains change randomly. We propose that their values theoretically change as a tri-variant 2 nd -order Markov chain process. States of Markov chain must be selected such that any sudden change is avoided. Important result of this modeling is that epileptic behavior of a cortical area may appear in various manners not in a unique one. Thus different observations in seizure onset all are validated and it is proved that they do not contradict each other.

关键词： Brain modeling Epilepsy Electroencephalography Neurons Signal generators Stochastic processes Neural engineering Digital signal processing Electronic mail Synchronous generators

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Decision Level Fusion of Colour Histogram Based Classifiers for Clustering of Mouth Area Images

Decision Level Fusion of Colour Histogram Based Classifiers ...

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International Conference on Digital Image processing, ICDIP

作者： Fahimeh Salimi Mohammad T. Sadeghi Signal Processing Research Laboratory Department of Electrical and Computer Engineering Engineering Research Centre Yazd University Yazd Iran

It is well known that in many situations combining diverse classifiers can improve the performance of a classification system. In this paper, a new histogram based lip segmentation technique is proposed considering local kernel histograms in different illumination invariant colour spaces. The histogram is computed in local areas using two Gaussian kernels; one in the colour space and the other in the spatial domain. Using the estimated histogram, the posterior probability associated to non-lip class is then computed for each pixel. This process is performed considering different colour spaces. A weighted averaging method is then used for fusing the posterior probability values. As the result a new score is obtained which is used for labeling the pixels as lip or non-lip. The advantage of the proposed method is that the segmentation process is totally unsupervised. So, the method is robust against different variations such as variation in lip shape, skin colour, facial hair, illumination, etc. Moreover, an improved performance is achieved by fusing colour information.

关键词： Histograms Mouth Kernel Lighting Diversity reception Image segmentation Color Labeling Robustness Shape

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A fusion-based approach for tolerating faults in finite state machines

A fusion-based approach for tolerating faults in finite stat...

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International Symposium on parallel and Distributed processing (IPDPS)

作者： Vinit Ogale Bharath Balasubramanian Vijay K. Garg Parallel and Distributed Systems Laboratory Department of Electrical and Computer Engineering University of Texas Austin USA IBM India Research Laboratory New Delhi India

ISBN: (纸本)9781424437511

Given a set of n different deterministic finite state machines (DFSMs) modeling a distributed system, we examine the problem of tolerating f crash or Byzantine faults in such a system. The traditional approach to this problem involves replication and requires n middot f backup DFSMs for crash faults and 2 middot n middot f backup DFSMs for Byzantine faults. For example, to tolerate two crash faults in three DFSMs, a replication based technique needs two copies of each of the given DFSMs, resulting in a system with six backup DFSMs. In this paper, we question the optimality of such an approach and present an approach called (f, m)-fusion that permits fewer backups than the replication based approaches. Given n different DFSMs, we examine the problem of tolerating f faults using just m additional DFSMs. We introduce the theory of fusion machines and provide an algorithm to generate backup DFSMs for both crash and Byzantine faults. We have implemented our algorithms in Java and have used them to automatically generate backup DFSMs for several examples.

关键词： Automata computer crashes Laboratories Concurrent computing Distributed computing Fusion power generation Standby generators Thermal sensors Counting circuits Java

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Incremental learning in nonstationary environments with controlled forgetting

Incremental learning in nonstationary environments with cont...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ryan Elwell Robi Polikar Signal Processing and Pattern Recognition Laboratory Electrical and Computer Engineering Department Rowan University Glassboro NJ USA

We have recently introduced an incremental learning algorithm, called Learn ++ .NSE, designed for Non-Stationary Environments (concept drift), where the underlying data distribution changes over time. With each dataset drawn from a new environment, Learn ++ .NSE generates a new classifier to form an ensemble of classifiers. The ensemble members are combined through a dynamically weighted majority voting, where voting weights are determined based on classifiers' age-adjusted accuracy on current and past environments. Unlike other ensemble-based concept drift algorithms, Learn ++ .NSE does not discard prior classifiers, allowing potentially cyclical environments to be learned more effectively. While Learn ++ .NSE has been shown to work well on a variety of concept drift problems, a potential shortcoming of this approach is the cumulative nature of the ensemble size. In this contribution, we expand our analysis of the algorithm to include various ensemble pruning methods to introduce controlled forgetting. Error or age-based pruning methods have been integrated into the algorithm to prevent potential out-voting from irrelevant classifiers or simply to save memory over an extended period of time. Here, we analyze the tradeoff between these precautions and the desire to handle recurring contexts (cyclical data). Comparisons are made using several scenarios that introduce various types of drift.

关键词： Neutron spin echo Algorithm design and analysis Voting

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Comparison between noise reduction algorithms for speech signals using auditory masking effects

Comparison between noise reduction algorithms for speech sig...

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IEEE GCC Conference & Exhibition

作者： Mehdi Yektaeian Rassoul Amirfattahi Digital Signal Processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

Auditory masking is aggressively exploited by algorithms used for the lossy compression of audio signals. In compression of audio signals, the intent is to hide the noise introduced by the coding below the masking threshold, thus making the noise inaudible. This will render the coding process transparent, enabling better compression without audible degradation of the signal. In this article, we show that using masking properties of the hearing system allows for improved noise reduction. A novel method for noise reduction in speech signals is proposed. This method is shown to outperform non-auditory based methods, and compares well with other perceptually motivated noise reduction methods. It is found that the proposed method, Soulodre's PNRF combined with the ITU's PEAQ auditory model, have more musical noise but less signal distortion than the method proposed by Tsoukalas, which obtain marginally better results in informal testing results.

关键词： Signal to noise ratio Noise reduction Speech Speech enhancement Masking threshold

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Noise reduction algorithm for robust speech recognition using MLP neural network

Noise reduction algorithm for robust speech recognition usin...

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Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA

作者： Masoumeh P. Ghaemmaghami Farbod Razzazi Hossein Sameti Saeed Dabbaghchian Bagher BabaAli Department of Electrical Engineering Science & Research Branch Azad University Tehran Iran Speech Processing Laboratory Department of Computer Engineering Sharif University of Technology Iran Department of Computer Engineering Speech Processing Lab Tehran Iran

We propose an efficient and effective nonlinear feature domain noise suppression algorithm, motivated by the minimum mean square error (MMSE) optimization criterion. Multi layer perceptron (MLP) neural network in the log spectral domain minimizes the difference between noisy and clean speech. By using this method as a pre-processing stage of a speech recognition system, the recognition rate in noisy environments is improved. We can extend the application of the system to different environments with different noises without re-training it. We need only to train the preprocessing stage with a small portion of noisy data which is created by artificially adding different types of noises from the NOISEX-92 database to the TIMIT speech database. Experimental results show that the proposed method can achieve significant improvement of recognition rates.

关键词： Noise reduction Noise robustness Speech recognition Neural networks Working environment noise Speech enhancement Feature extraction Application software Speech processing Databases

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Signal processing for neural spike trains

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Computational intelligence and neuroscience 2010年第1期2010卷 698751页

作者： Theodore W Berger Zhe Sage Chen Andrzej Cichocki Karim G Oweiss Rodrigo Quian Quiroga Nitish V Thakor Department of Biomedical Engineering Viterbi School of Engineering University of Southern California Los Angeles CA 90089 USA Neuroscience Statistics Research Laboratory Massachusetts Institute of Technology Cambridge MA 02139 USA Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Wako-shi Saitama 351-0198 Japan Department of Electrical and Computer Engineering Michigan State University MI 48824 USA Department of Engineering University of Leicester Leicester LE1 7RH UK School of Medicine Johns Hopkins University Baltimore MD 21205 USA

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Fuzzy controller for cooperative object pushing with variable line contact

Fuzzy controller for cooperative object pushing with variabl...

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International Conference on Mechatronics (ICM)

作者： Mahsa Aliakbar Golkar Sarah Taghavi Namin Hossein Aminaiee Control and Intelligent Processing Center of Excellence Robotics and AI Laboratory Department of Electrical and Computer Engineering University of Tehran Iran

Designing an appropriate cooperation protocol in multi-robot systems such as multi-robot object manipulation systems is a challenging task. In this paper designing and implementing a cooperation protocol between two robots pushing an object toward an arbitrary goal configuration is investigated. The proposed method benefits from task decoupling which simplifies the cooperation protocol design. Each robot gets its proper action from a particular fuzzy inference system independently. The fuzzy controllers outputs are low-level robot commands by which the need to a robot path planning algorithm is eliminated. Simulation results show that robots could push the object to the goal configuration cooperatively. Experiments have been conducted to approve the proposed system.

关键词： Fuzzy control Robot kinematics Protocols Fuzzy systems Electric variables control Control systems Multirobot systems Path planning Inference algorithms Mobile robots

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Kernel-based Linear Spectral Mixture Analysis for hyperspectral image classification

Kernel-based Linear Spectral Mixture Analysis for hyperspect...

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Workshop on Hyperspectral Image and Signal processing: Evolution in Remote Sensing, WHISPERS

作者： Keng-Hao Liu Englin Wong Chein-I Chang Remote Sensing Signal and Image Processing Laboratory the Department of Computer Science and Electrical Engineering Department University of Maryland Baltimore MD USA Department of Electrical Engineering National Chung Hsing University Taichung Taiwan

Linear spectral mixture analysis (LSMA) has been widely used in remote sensing community. Recently, kernel-based approaches have received considerable interest in hyperspectral image analysis where nonlinear kernels are used to resolve the issue of nonlinear separability in classification. This paper extends the LSMA to kernel-based LSMA where three least squares-based LSMA techniques, least squares orthogonal subspace projection (LSOSP), non-negativity constrained least squares (NCLS) and fully constrained least squares (FCLS) are extended to their kernel counterparts, KLSOSP, KNCLS and KFCLS.

关键词： Image analysis Spectral analysis Hyperspectral imaging Image classification Least squares methods Hyperspectral sensors Kernel Subspace constraints Remote sensing Image resolution

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