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On the extraction of the snore acoustic signal by independent component analysis

On the extraction of the snore acoustic signal by independen...

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2nd IASTED international conference on Biomedical Engineering

作者： Vrins, F Deswert, J Bouvy, D Bouillon, V Lee, JA Eugène, C Verleysen, M Catholic Univ Louvain Microelect Lab Machine Learning Grp B-1348 Louvain Belgium

ISBN: (纸本)088986408X

Physicians are interested in the acoustic signal of snore, because it allows them to diagnose the patient and eventually to avoid several dangerous accidents. Today, its measure is not satisfactory for various reasons. In this paper, we explore a new way to measure this signal: Blind Source Separation (BSS). We give encouraging results of source separation in this application but also stress the obstacles which prevent a perfect separation when BSS is achieved by the classic linear, instantaneous and un-noiseless model of Independent Component Analysis, an undoubtfully very promising signal processing method in the biomedical world.

关键词： snoring non-invasive measurement independent component analysis

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Serve system intelligent control based on a novel associative memory system

Serve system intelligent control based on a novel associativ...

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international IEEE conference on Intelligent Systems, IS

作者： Wang Jun Song Department of Automation Engineering Tianjin University of Technical Education China

ISBN: (纸本)0780382781

This paper firstly proposes a novel associative memory system based on discrete Taylor series-DTS-AMS, which is capable of implementing error-free approximations to multi-variable polynomial functions of arbitrary order. The advantages it offers over conventional CMAC neural network are: high-precision of learning, much smaller memory requirement without the data-collision problem, much less computational effort for training and faster convergence rates than that attainable with multi-layer BP neural networks. Secondly, a serve system intelligent control scheme based on DTS-AMS is designed, where DTS-AMS is employed to learn the inverse dynamic model of the serve system. A set of numerical simulations have been conducted, and simulation results have shown that the novel neural network based control strategy is feasible and efficient. The novel neural network has great potential in the application areas of realtime intelligent control for complex system.

关键词： Intelligent control Associative memory Neural networks Polynomials Taylor series signal processing algorithms Multi-layer neural network Computer networks Convergence Interpolation

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2nd international conference on Artificial Immune Systems, ICARIS 2003

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2nd international conference on Artificial Immune Systems, ICARIS 2003

ISBN: (纸本)3540407669

The proceedings contain 28 papers. The special focus in this conference is on Applications of Artificial Immune Systems. The topics include: Use of an artificial immune system for job shop scheduling;an artificial immune system for multimodality image alignment;bioinformatics data analysis using an artificial immune network;an investigation of the negative selection algorithm for fault detection in refrigeration systems;immunologic control framework for automated material handling;an immune learning classifier network for autonomous navigation;an artificial immune system approach to mutation testing;memory and selectivity in evolving scale-free immune networks;biomolecular immunocomputing;signal processing by an immune type tree transform;index design by immunocomputing;immune-based framework for exploratory bio-information retrieval from the semantic web;an artificial immune system approach to semantic document classification;a danger theory inspired approach to web mining;meta-stable memory in an artificial immune network;improved pattern recognition with artificial clonal selection;inspirations from the danger theory;artificial immune systems and the grand challenge for non-classical computation;implications for immune network models and clonal selection;revisiting the foundations of artificial immune systems and complementary dual detectors for effective classification.

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Controlling a large-scale industrial oven by monitoring the food quality, both internally and externally, using an optical fibre based system

Controlling a large-scale industrial oven by monitoring the ...

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2nd IEEE international conference on Sensors

作者： O'Farrell, M Lewis, E Flanagan, C Lyons, WB Jackman, N Univ Limerick Limerick Ireland

ISBN: (纸本)0780381335

An Optical fibre based sensor system has been developed for the purpose of examining the colour of food products online as they cook in a large-scale industrial oven. By classing the measured colours it is possible to automatically determine if the food is cooked to an optimum perceived colour. Developments have been made on previous work by the authors [1,2] by further examining the internal colour of the food and also looking at food that does not have an even colour externally. Spectroscopic techniques are employed to determine the colour and this signal is interrogated using an Artificial Neural Network. The resultant output spectral patterns can therefore be quantitatively classified and thus categorized.

关键词： optical fibre sensor artificial neural network pattern recognition colour classification feed forward networks food processing industry back propagation learning

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A cascade form blind source separation connecting source separation and linearization for nonlinear mixtures

A cascade form blind source separation connecting source sep...

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international Joint conference on Neural Networks (IJCNN)

作者： K. Nakayama A. Hirano T. Nishiwaki Department of Information Systems Engineering Faculty of Engineering Kanazawa University Kanazawa Japan

A network structure and its learning algorithm have been proposed for blind source separation applied to nonlinear mixtures. The network has a cascade form consists of a source separation block and a linearization block in this order. The conventional learning algorithm is employed for the separation block. A new learning algorithm is proposed for the linearization block assuming 2nd-order nonlinearity. After, source separation, the outputs include the nonlinear components for the same signal source. This nonlinearity is suppressed through the linearization block. Parameters in this block are iteratively adjusted based on a process of solving a 2nd-order equation of a single variable. Simulation results, using 2-channel speech signals and an instantaneous nonlinear mixing process, show good separation performance.

关键词： Blind source separation Joining processes Source separation signal processing algorithms Iterative algorithms signal processing Separation processes Spline Information systems Nonlinear equations

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Cortical plasticity contributing to variations in human performance ability

Cortical plasticity contributing to variations in human perf...

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IEEE international conference on Development and learning, ICDL

作者： M.M. Merzenich Keck Center for Integrative Neurosciences University of California San Francisco USA

Summary form only given. Studies conducted in developing and adult rats and monkeys have been designed to determine sources of variation in performance ability in infant and young adult brains. They indicate the importance of variations in signal-to-noise conditions. Brain plasticity models have also been applied to identify catastrophic failure modes of self-organizing brain systems. On the bases of these studies, novel rehabilitation strategies have been developed that are designed to ameliorate the symptoms of human developmental impairments and disabilities. For children with language and reading impairments, dramatic behavioral improvements are achieved by this training. Those behavioral changes are paralleled by a substantial physiological re-normalization documented by EEG, MEG and fMRI recording methods.

关键词： Neuroplasticity Humans Pediatrics signal processing Animals Rats Process control Brain modeling Autism Electric breakdown

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Support vector machines on the space of Walsh functions and their properties

Support vector machines on the space of Walsh functions and ...

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international Symposium on Image and signal processing and Analysis

作者： A. Fazekas C. Kotropoulos I. Buciu I. Pitas Department of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9539676940

Support vector machine is a special kind of learning machine, proposed by Vapnik. The learning capability of support vector machines depends on the Vapnik-Chervonenkis (VC) dimension of the kernel function used. In this paper, we construct a new kernel function for support vector machine, which is based on Walsh functions. We prove some theoretical results related to the VC-dimension of the support vector machines which are built in the space of the Walsh functions. First experimental results for face detection are reported.

关键词： Support vector machines Kernel Face detection machine learning Pattern recognition Informatics Testing Probability density function Hilbert space Polynomials

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Neuro-fuzzy filters based on recursive processing and genetic learning

Neuro-fuzzy filters based on recursive processing and geneti...

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international Symposium on Image and signal processing and Analysis

作者： F. Russo D.E.E.I University of Trieste Italy

ISBN: (纸本)9539676940

Neuro-fuzzy filters based on genetic learning are a recently introduced class of nonlinear operators that aim at exploiting the powerful paradigms of computational intelligence. These filters adopt fuzzy reasoning to model the noise removal process and then perform an effective noise cancellation without blurring the image details. In this paper, we focus on the latest generation of neuro-fuzzy filters that adopt a multiple-output architecture. These filters are composed of several subnetworks that process different subsets of input data adopting a serial or a parallel approach. Since the filtering action is recursive, even different processing strategies can be combined in the same filtering architecture. As a result, the most appropriate filtering behavior can be learned from a set of training data.

关键词： Filters Filtering Noise cancellation Fuzzy systems Computational intelligence Training data Artificial neural networks Genetic algorithms Humans Fuzzy sets

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A computational allegory for V1

A computational allegory for V1

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international Symposium on Image and signal processing and Analysis

作者： A.T. Puga Secção de Matemática DEMEGI FEUP and INESC Porto Porto Portugal

ISBN: (纸本)9539676940

This contribution introduces a computational allegory for V1 in the task of static image coding. It can be considered an extrapolation of previous V1 models based on unsupervised learning but envisaging two new objectives. The first is a contribution to the discussion of the quantity of V1 cells. The second is the estimation of the quantity of cells within a V1 hypercolumn needed to present to higher-levels the early coding of the correspondent retinal image portion. It is broadly accepted that the quantity of V1 cells coding the correspondent retinal image must be sparse (low dimension) but avoiding pure sparsity (dimension one). The concrete value of that (mean) dimension is still an open issue. Consequently, it is opportune to study the question: "what is the dimension of V1 coding?". An important side effect of a possible answer could be a contribution to justify the large relative quantity of center-symmetric and simple V1 cells in comparison with the quantity of LGN cells. The implemented allegory is based on unsupervised learning. During the learning phase, a dictionary of image blocks is built by using unsupervised learning principals - principal component analysis (PCA), symmetric component analysis (SCA) and independent component analysis (ICA) operating on small learning sets. During coding, the previously learned dictionary is used to perform matching pursuit in order to code new incoming image blocks as linear combinations of some dictionary components. The results so far obtained support a first provocative answer: "a dimension around 4?".

关键词： Image coding Unsupervised learning Dictionaries Independent component analysis Retina Principal component analysis Extrapolation Concrete Image analysis Matching pursuit algorithms

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EvoWorkshops 2000: 2nd European Workshop on Evolutionary Computation in Image Analysis and signal processing, EvoIASP 2000, 1st European Workshop on Evolutionary Computation in Systems, Control and Drives in Industry, Evo-SCOndI 2000, 2nd European Workshop on Evolutionary Telecommunications, EvoTel 2000, 1st European Workshop on Evolutionary Scheduling and Timetabling, EvoStim 2000, 3rd European Workshop on Evolutionary Robotics, EvoRob 2000 and 1st European Workshop on Evolutionary Aeronautics, EvoFlight 2000 held in conjunction with European conference on Genetic Programming, EuroGP 2000 and 3rd international conference on Evolvable Systems, ICES 2000

引用

EvoWorkshops 2000: 2nd European Workshop on Evolutionary Computation in Image Analysis and signal processing, EvoIASP 2000, 1st European Workshop on Evolutionary Computation in Systems, Control and Drives in Industry, Evo-SCOndI 2000, 2nd European Workshop on Evolutionary Telecommunications, EvoTel 2000, 1st European Workshop on Evolutionary Scheduling and Timetabling, EvoStim 2000, 3rd European Workshop on Evolutionary Robotics, EvoRob 2000 and 1st European Workshop on Evolutionary Aeronautics, EvoFlight 2000 held in conjunction with European conference on Genetic Programming, EuroGP 2000 and 3rd international conference on Evolvable Systems, ICES 2000

ISBN: (纸本)3540673539

The proceedings contain 37 papers. The special focus in this conference is on EvoIASP Talks and EvoIASP Posters. The topics include: Special purpose image convolution with evolvable hardware;stereoscopic vision for a humanoid robot using genetic programming;a faster genetic clustering algorithm;scene interpretation using semantic nets and evolutionary computation;evolutionary wavelet bases in signal spaces;the ultra high tech approach;sound localization for a humanoid robot by means of genetic programming;on the scalability of genetic algorithms to very large-scale feature selection;combining evolutionary, connectionist, and fuzzy classification algorithms for shape analysis;experimental determination of drosophila embryonic coordinates by genetic algorithms, the simplex method, and their hybrid;a genetic algorithm with local search for solving job shop problems;distributed learning control of traffic signals;time series prediction by growing lateral delay neural networks;trajectory controller network and its design automation through evolutionary computing;evolutionary computation and nonlinear programming in multi-model-robust control design and benchmarking cost-assignment schemes for multi-objective evolutionary algorithms.

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