Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing
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Signal reconstruction from sampled data using neural network
- Trang 707-715
For reconstructing a signal from sampling data, the method based on Shannon's sampling theorem is usually employed. The reconstruction error appears when the signal does not satisfy the Nyquist condition. This paper proposes a new reconstruction method by using a linear perceptron and multilayer perceptron as FIR filter. The perceptron, which has weights obtained by learning when adapting the orig...... hiện toàn bộ
#Signal reconstruction #Neural networks #Image reconstruction #Sampling methods #Finite impulse response filter #Frequency #Adaptive filters #Image sampling #Information retrieval #Physics
A probabilistic approach for long read-length DNA sequence analysis
- Trang 45-56
This paper introduces a new algorithm for DNA sequence analysis, based on the use of a reference DNA sequence for the estimation of base positions, and a probabilistic modelling of trace peaks. The new algorithm has been applied to long read-length DNA sequences and its performance has been compared to the base-calling program Phred. The results reported in this paper, after cross-matching with a ...... hiện toàn bộ
#DNA #Bioinformatics #Genomics #Signal processing algorithms #Phase estimation #Image sequence analysis #Signal analysis #Libraries #Algorithm design and analysis #Humans
A two-stage SVM architecture for predicting the disulfide bonding state of cysteines
- Trang 25-34
Cysteines may form covalent bonds, known as disulfide bridges, that have an important role in stabilizing the native conformation of proteins. Several methods have been proposed for predicting the bonding state of cysteines, either using local context or using global protein descriptors. In this paper we introduce an SVM based predictor that operates in two stages. The first stage is a multi-class...... hiện toàn bộ
#Support vector machines #Bonding #Amino acids #Proteins #Bridges #Neural networks #Electronic mail #Support vector machine classification #Accuracy #Genomics
Unsupervised reduction of the dimensionality followed by supervised learning with a perceptron improves the classification of conditions in DNA microarray gene expression data
- Trang 77-86
This manuscript describes a combined approach of unsupervised clustering followed by supervised learning that provides an efficient classification of conditions in DNA array gene expression experiments (different cell lines including some cancer types, in the cases shown). Firstly the dimensionality of the dataset of gene expression profiles is reduced to a number of non-redundant clusters of co-e...... hiện toàn bộ
#Supervised learning #Gene expression #DNA #Cancer #Neural networks #Principal component analysis #Clustering algorithms #Support vector machines #Support vector machine classification #Biotechnology
Simple algorithms for decorrelation-based blind source separation
- Trang 545-554
We present simple adaptive algorithms that perform blind source separation for spatially-independent and temporally-correlated source signals. The proposed algorithms are modified versions of a well-known natural gradient prewhitening scheme, and the simplest version has almost the same complexity as this prewhitening method. We provide a stationary point analysis of our schemes, proving that the ...... hiện toàn bộ
#Decorrelation #Blind source separation #Source separation #Statistics #Iterative algorithms #Adaptive algorithm #Analysis of variance #Performance analysis #Gradient methods #Algorithm design and analysis
Metric-based model selection for time-series forecasting
- Trang 13-22
Metric-based methods, which use unlabeled data to detect gross differences in behavior away from the training points, have recently been introduced for model selection, often yielding very significant improvements over alternatives (including cross-validation). We introduce extensions that take advantage of the particular case of time-series data in which the task involves prediction with a horizo...... hiện toàn bộ
#Predictive models #Linear regression #Input variables #Testing #Training data #Machine learning
Fast edge-based stereo matching algorithm based on search space reduction
- Trang 587-596
The reduction of the search region in stereo correspondence can increase the performance of the matching process, in the context of execution time and accuracy. For edge-based stereo matching, we establish the relationship between the search space and parameters like relative displacement of the edges, the disparity under consideration, the image resolution, the CCD dimensions and the focal length...... hiện toàn bộ
#Cameras #Space technology #Layout #Electronic mail #Image resolution #Charge coupled devices #Robot vision systems #Stereo vision #Wavelet transforms #Joining processes
A comparative study of genetic sequence classification algorithms
- Trang 57-66
Classification of genetic sequence data available in public and private databases is an important problem in using, understanding, retrieving, filtering and correlating such large volumes of information. Although a significant amount of research effort is being spent internationally on this problem, very few studies exist that compare different classification approaches in terms of an objective an...... hiện toàn bộ
#Genetics #Classification algorithms #Sequences #Databases #Clustering algorithms #Artificial neural networks #Information retrieval #Information filtering #Information filters #Frequency
Language model adaptation in speech recognition using document maps
- Trang 627-636
We present speech experiments that were carried out to evaluate a topically focusing language model in large vocabulary speech recognition. An ordered topical clustering is first computed as a self-organized mapping of a large document collection. Language models are then trained for each text cluster or for several neighboring clusters. The obtained organized collection of language models is effi...... hiện toàn bộ
#Natural languages #Adaptation model #Speech recognition #Vocabulary #Probability #Intelligent networks #Neural networks #Speech analysis #Databases #Ultraviolet sources
Face recognition using kernel principal component analysis and genetic algorithms
- Trang 337-343
Kernel principal component analysis (KPCA) as a powerful nonlinear feature extraction method has proven as a preprocessing step for classification algorithm. A face recognition approach based on KPCA and genetic algorithms (GAs) is proposed. By the use of the polynomial functions as a kernel function in KPCA, the high order relationships can be utilized and the nonlinear principal components can b...... hiện toàn bộ
#Face recognition #Kernel #Principal component analysis #Genetic algorithms #Support vector machines #Support vector machine classification #Feature extraction #Classification algorithms #Polynomials #Spatial databases