7,878 research outputs found
A New Ensemble Learning Method for Temporal Pattern Identification
AbstractIn this paper we present a method for identification of temporal patterns predictive of significant events in a dynamic data system. A new hybrid model using Reconstructed Phase Space (MRPS) and Hidden Markov Model (HMM) is applied to identify temporal patterns. This method constructs phase space embedding by using individual embedding of each variable sequences. We also employ Hidden Markov Models (HMM) to the multivariate sequence data to categorize multi-dimensional data into three states, e.g. normal, patterns and events. A support vector machine optimization method is used to search an optimal classifier to identify temporal patterns that are predictive of future events. We performed two experimental applications using chaotic time series and natural gas usage series related to the natural gas usage forecasting problem. Experiments show that the new method significantly outperforms the original RPS framework and neural network method
Time-Domain Isolated Phoneme Classification Using Reconstructed Phase Spaces
This paper introduces a novel time-domain approach to modeling and classifying speech phoneme waveforms. The approach is based on statistical models of reconstructed phase spaces, which offer significant theoretical benefits as representations that are known to be topologically equivalent to the state dynamics of the underlying production system. The lag and dimension parameters of the reconstruction process for speech are examined in detail, comparing common estimation heuristics for these parameters with corresponding maximum likelihood recognition accuracy over the TIMIT data set. Overall accuracies are compared with a Mel-frequency cepstral baseline system across five different phonetic classes within TIMIT, and a composite classifier using both cepstral and phase space features is developed. Results indicate that although the accuracy of the phase space approach by itself is still currently below that of baseline cepstral methods, a combined approach is capable of increasing speaker independent phoneme accuracy
Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences
We present a new method for nonlinear prediction of discrete random sequences
under minimal structural assumptions. We give a mathematical construction for
optimal predictors of such processes, in the form of hidden Markov models. We
then describe an algorithm, CSSR (Causal-State Splitting Reconstruction), which
approximates the ideal predictor from data. We discuss the reliability of CSSR,
its data requirements, and its performance in simulations. Finally, we compare
our approach to existing methods using variable-length Markov models and
cross-validated hidden Markov models, and show theoretically and experimentally
that our method delivers results superior to the former and at least comparable
to the latter.Comment: 8 pages, 4 figure
Data based identification and prediction of nonlinear and complex dynamical systems
We thank Dr. R. Yang (formerly at ASU), Dr. R.-Q. Su (formerly at ASU), and Mr. Zhesi Shen for their contributions to a number of original papers on which this Review is partly based. This work was supported by ARO under Grant No. W911NF-14-1-0504. W.-X. Wang was also supported by NSFC under Grants No. 61573064 and No. 61074116, as well as by the Fundamental Research Funds for the Central Universities, Beijing Nova Programme.Peer reviewedPostprin
Statistical analysis on detecting recombination sites in DNA-beta satellites associated with the old world geminiviruses
Although an exchange of genetic information by recombination plays an
important role in the evolution of viruses, it is not clear how it generates
diversity. {\it Geminiviruses} are plant viruses which have ambisense
single-stranded circular DNA genomes and one of the most economically important
plant viruses in agricultural production. Small circular single-stranded DNA
satellites, termed DNA-, have recently been found associated with some
geminivirus infections. In this paper we analyze a satellite molecule
DNA- of geminiviruses for recombination events using phylogenetic and
statistical analysis and we find that one strain from ToLCMaB has a
recombination pattern and is possibly recombinant molecule between two strains
from two species, PaLCuB-[IN:Chi:05] (major parent) and ToLCB-[IN:CP:04] (minor
parent).Comment: 8 figures and 2 tables. To appear in Frontiers in Systems Biolog
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