Hidden Markov processes

IEEE Transactions on Information Theory

Volumn 48, Issue 6, 2002, Pages 1518-1569

  Ephraim, Yariv ^a,b   Merhav, Neri ^a,c  

^a IEEE   (United States)

^b George Mason University   (United States)

^c TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Baum Petrie algorithm; Entropy ergodic theorems; Finite state channels; Hidden Markov models; Identifiability; Kalman filter; Maximum likelihood (ML) estimation; Order estimation; Recursive parameter estimation; Switching autoregressive processes; Ziv inequality

Indexed keywords

HIDDEN MARKOV PROCESSES (HMP);

ALGORITHMS; DECODING; KALMAN FILTERING; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION;

COMMUNICATION CHANNELS (INFORMATION THEORY);

EID: 0036612017     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIT.2002.1003838     Document Type: Article

References (333)

1. Ergodic and mixing properties of infinite memory channels
2. A hidden Markov model for an inventory system with perishable items
3. The generalized distributive law
4. A new look at the statistical model identification
5. Detection of binary Markov sources over channels with additive Markov noise
6. A two-state Markov mixture model for a time series of epileptic seizure counts
7. Estimation of kinetic rate constants from multi-channel recordings by a direct fit of the time series
8. A theory of adaptive pattern classifiers
9. Tree encoding of speech
10. Real-number convolutional codes for speech-like quasistationary sources
11. From Wiener to hidden Markov models
12. Over-the-horizon radar target localization using a hidden Markov model estimated from ionosonde data
13. Simulated annealing for maximum a posteriori parameter estimation of hidden Markov models
14. A recursive algorithm for the Bayes solution of the smoothing problem
15. Robust and fast failure detection and prediction for fault-tolerant communication network
16. Optimal decoding of linear codes for minimizing symbol error rate
17. Decoding for channels with insertions, deletions, and substitutions with applications to speech recognition
18. A maximum likelihood approach to continuous speech recognition
19. Maximum mutual information estimation of hidden Markov model parameters for speech recognition
20. The DRAGON system - An overview
21. Stochastic models for ion channels: Introduction and bibliography
22. The strong ergodic theorem for densities: Generalized Shannon-McMillan-Breiman theorem
23. The minimum description length principle in coding and modeling
24. Statistical inference for probabilistic functions of finite state Markov chains
25. An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology
26. Growth transformations for functions on manifolds
27. A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains
28. An inequality and associated maximization technique in statistical estimation for probabilistic functions of Markov processes
29. Near Shannon limit error-correcting coding and decoding: Turbo-codes
30. Near optimum error correcting coding and decoding: Turbo-codes
31. On the statistical analysis of dirty pictures
32. Inference in hidden Markov models I: Local asymptotic normality in the stationary case
33. Asymptotic normality of the maximum-likelihood estimator for general hidden Markov models
34. Bayesian estimation of switching ARMA models
35. Approximations for the entropy for functions of Markov chains
36. The entropy of functions of finite-state Markov chains
37. On the identifiability problem for functions of finite Markov chains
38. Proof of Shannon's transmission theorem for finite-state indecomposable channels
39. On identification of states of a sequence generated by a hidden Markov model
40. Strict stationarity of generalized autoregressive processes
41. n with stationary coefficients
42. Spatial filtering of superimposed convolutional coded signals
43. A reduced-complexity online state sequence and parameter estimator for superimposed convolutional coded signals
44. A soft output hybrid algorithm for ML/MAP sequence estimation
45. Asymptotic behavior of classification maximum likelihood estimates
46. A Markovian function of a Markov chain
47. A hidden Markov model approach to neuron firing patters
48. Identification of state-calculable functions of finite Markov chains
49. Hidden Markov models for English
50. On receiver structures for channels having memory
51. Hidden Markov models for the burst error statistics of Viterbi decoding
52. Segmental GPD training of HMM based speech recognizer
53. Characterization of single channel currents using digital signal processing techniques based on hidden Markov models
54. Adaptive processing techniques based on hidden Markov models for characterizing very small channel currents buried in noise and deterministic interferences
55. Stochastic models for Heterogeneous DNA sequences
56. Stochastic maximum likelihood methods for semi-blind channel estimation
57. Use of hidden Marker models for electrocardiographic signal analysis
58. On-line identification of hidden Marker models via recursive prediction error techniques
59. The voice of the computer is heard in the land and it listens too!
60. Wavelet-based statistical signal processing using hidden Markov models
61. Information geometry and alternating maximization procedures
62. Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems
63. The method of types
64. The consistency of the BIC Markov order estimator
65. Universal noiseless coding
66. Remarks on linear and nonlinear filtering
67. Parameter estimation of partially observed continuous time stochastic processes via the EM algorithm
68. On the parameters estimation of continuous-time ARMA processes from noisy observations
69. Maximum a posteriori estimation of time-varying ARMA processes from noisy observations
70. Maximum likelihood from incomplete data via the EM algorithm
71. Baum's forward-backward algorithm revisited
72. A note on the observation of a Markov source through a noisy channel
73. Functions of finite Markov chains
74. Sufficient conditions for a stationary process to be a function of a finite Markov chain
75. Exchangeable processes which are functions of stationary Markov chain
76. A characterization of a class of functions of finite Markov chains
77. Estimation of finite mixture distributions through Bayesian sampling
78. Stochastic EM: Method and application
79. Information transmission over a finite buffer channel
80. Asymptotics of the maximum likelihood estimator for general hidden Markov models
81. Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime
82. Observation of a Markov source through a noisy channel
83. Speech processing in a high ambient noise environment
84. An algorithm for the design of labeled-transition finite-state vector quantizers
85. The influence of initial conditions on maximum likelihood estimation of the parameters of a binary hidden Markov model
86. Estimates of error rates for codes on burst-noise channels
87. New finite-dimensional filters and smoothers for noisily observed Markov chains
88. New finite-dimensional filters for parameter estimation of discrete-time linear Gaussian models
89. A minimum discrimination information approach for hidden Markov modeling
90. On the relations between modeling approaches for speech recognition
91. Speech enhancement using state dependent dynamical system model
92. Lower and upper bounds on the minimum mean square error in composite source signal estimation
93. Statistical model-based speech enhancement systems
94. On second-order statistics and linear estimation of cepstral coefficients
95. Functions of Markov chains
96. On asymptotically efficient recursive estimation
97. An algorithm to find the global optimum of left-to-right hidden Markov model parameters
98. Universal decoding for channels with memory
99. Universal composite hypothesis testing: A competitive minimax approach
100. Random coefficient autoregressive processes: A Markov chain analysis of stationarity and finiteness of moments
101. The Markov-modulated Poisson process (MMPP) cookbook
102. Universal codes for a class of composite sources
103. Limit theorems for slowly varying composite sources
104. Asymptotically mean stationary channels
105. On universal coding for classes of composite and remote sources with memory
106. Partially hidden Markov models
107. Generalization of the Viterbi algorithm
108. The Viterbi algorithm
109. Conditions under which a given process is a function of a Markov chain (Abstract)
110. On white noises driven by hidden Markov chains
111. Ergodicity of autoregressive processes with Markov-switching and consistency of the maximum-likelihood estimator
112. Maximum likelihood estimation and identification directly from single-channel recordings
113. Bayesian restoration of single channel patch clamp recordings
114. A Poisson process whose rate is a hidden Markov process
115. Turbo decoding of hidden Markov sources with unknown parameters
116. Products of random matrices
117. Automatic classification of environmental noise events by hidden Markov models
118. On the identifiability problem for functions of finite Markov chains
119. Capacity of a burst-noise channel
120. Text-independent speaker identification
121. Likelihood-ratio tests for hidden Markov models
122. Switched scalar quantizers for hidden Markov sources
123. Capacity, mutual information, and coding for finite-state Markov channels
124. Asymptotically optimal filtering for a hidden Markov model
125. On filtering for a hidden Markov chain under square performance criterion
126. An inequality for rational functions with applications to some statistical estimation problems
127. Optimal simultaneous detection and estimation of filtered discrete semi-Markov chains
128. Rate distortion functions for finite-state finite-alphabet Markov sources
129. The ergodic decomposition of stationary discrete random processes
130. Asymptotically mean stationary measures
131. Rate-distortion speech coding with a minimum discrimination information distortion measure
132. Ergodicity of Markov channels
133. Quantization
134. Asymptotically optimal classification for multiple tests with empirically observed statistics
135. 2-D shape classification using hidden Markov models
136. A class of data traffic processes - Covarianee function characterization and related queuing results
137. A Markov modulated characterization of packetized voice and data traffic and related statistical multiplexer performance
138. On stochastie processes derived from Markov chains
139. State learning and mixing in entropy of hidden Markov processes and the Gilbert-Elliott channel
140. Recursive estimation in mixture models with Markov regime
141. Recursive estimation in switching autoregressions with a Markov regime
142. Computing the observed information in the hidden Markov model using the EM algorithm
143. Identifiability of Hidden Markov information sources and their minimum degrees of freedom
144. Time discretization of continuous-time filters and smoothers for HMM parameter estimation
145. A fast sequential decoding algorithm using a stack
146. Design of a linguistic statistical decoder for recognition of continuous speech
147. Continuous speech recognition by statistical methods
148. Asymptotic normality of the maximum likelihood estimator in state space models
149. Mixture autoregressive hidden Markov models for speech signals
150. The segmental k-means algorithm for estimating parameters of hidden Markov models
151. Discriminative learning for minimum error classification
152. Statistical and discriminative methods for speech recognition
153. Joint Parameter estimation and symbol detection for linear or nonlinear unknown channels
154. The Baum-Welch algorithm for the detection of time-unsynchronized rectangular PAM signals
155. Existence of moments in a stationary stochastic difference equation
156. Identification of a transition matrix of a Markov chain from noisy measurements of state
157. Bayesian classification of hidden Markov models
158. Some procedures for state estimation of a hidden Markov chain with two states
159. Asymptotic filtering for finite state Markov chains
160. Markov channels are asymptotically mean stationary
161. Strongly consistent code-based identification and order estimation for constrained finite-state model classes
162. Subadditive ergodic theory
163. Non-Gaussian state-space modeling of nonstationary time series
164. Analysis of multichannel patch clamp recordings by hidden Markov models
165. Hidden Markov models estimation via the most informative stopping times for the Viterbi algorithm
166. Comments on Kitagawa [189]
167. Modeling ECG signals with hidden Markov models
168. Hidden Markov model signal processing in presence of unknown deterministic interferences
169. On-line estimation of hidden Markov model parameters based on the Kutlback-Leibler information measure
170. Blind equalization Of IIR channels using hidden Markov models and extended least squares
171. A filtered EM algorithm for joint hidden Markov model and sinusoidal parameter estimation
172. Consistent estimation of linear and nonlinear autoregressive models with Markov regime
173. Adaptive nonlinear filters for narrow-band interference suppression in spread-spectrum CDMA systems
174. Hidden Markov models in computational biology applications to protein modeling
175. Maximum likelihood coordinate registration for over-the-horizon radar
176. Markov-switching vector autoregressions: Modelling, statistical inference, and applications to business cycle analysis
177. State space and hidden Markov models
178. On the universality of the LZ-based decoding algorithm
179. Reliable communication under channel uncertainty
180. A canonical representation for aggregated Markov processes
181. Exact likelihood evaluation in a Markov mixture model for time series of seizure counts
182. Bearing-only tracking for maneuvering sources
183. Exponential forgetting and geometric ergodicity in hidden Markov models
184. Maximum-penalized-likelihood estimation for independent and Markov-dependent mixture models
185. Consistent estimation of a mixing distribution
186. Maximum-likelihood estimation for hidden Markov models
187. An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition
188. Continuously variable duration hidden Markov models for automatic speech recognition
189. Image classification by two-dimensional hidden Markov model
190. An algorithm for vector quantizer design
191. Markov regime models for mixed distributions andswitching regressions
192. Recursive estimation of parameters in Markov-modulated Poisson processes
193. Maximum Likelihood estimation for multivariate observations of Markov sources
194. Order estimation and sequential universal data compression of a hidden Markov source by the method of mixtures
195. Estimation of hidden Markov model parameters by minimizing empirical error rate
196. Finding the observed information matrix when using the EM algorithm
197. GeneMark.hmm: New solutions for gene finding
198. Optimal adaptive estimation of sampled stochastic processes
199. What is a hidden Markov model?
200. A local limit theorem for hidden Markov chains
201. A fitting algorithm for Markov-modulated Poisson processes having two arrival rates
202. Hidden Markov modeling using a dominant state sequence with application to speech recognition
203. Universal classification for hidden Markov models
204. Universal coding with minimum probability of codeword length overflow
205. A Bayesian approach for classification of Markov sources
206. A Bayesian classification approach with application to speech recognition
207. Universal detection of messages via finite-state channels
208. A sequence-based approximate MMSE decoder for source coding over noisy channels using discrete hidden Markov models
209. A survey of partially observable Markov decision processes: Theory, models, and algorithm
210. Capacity and coding for the Gilbert-Elliott channels
211. Optimal solution of a training problem in speech recognition
212. Random coefficients autoregressive models: An introduction
213. High-performance connected digit recognition using maximum mutual information estimation
214. Compact encoding of stationary Markov sources
215. Low-delay optimal MAP state estimation in HMM's with application to symbol decoding
216. Probabilistic functions of finite state Markov chains
217. Optimal detection of discrete Markov sources over discrete memoryless channels - Applications to combined source-channel coding
218. Upper bounds on the probability of sequences emitted by finite-state sources and on the redundency of the Lempel-Ziv algorithm
219. Linear predictive hidden Markov models
220. Linear predictive hidden Markov models and the speech signal
221. Hidden Markov models: A guided tour
222. Texture classification using noncausal hidden Markov models
223. Estimation of parameters in hidden Markov models
224. A segmental k-means training procedure for connected word recognition
225. A tutorial on hidden Markov models and selected applications in speech recognition
226. Analysis, classification, and coding of multielectrode spike trains with hidden Markov models
227. Decision making in Markov chains applied to the problem of pattern recognition
228. Mixture densities, maximum likelihood and the EM algorithm
229. Modeling by shortest data description
230. Universal coding information prediction estimation
231. Bayesian estimation of hidden Markov chains: A stochastic implementation
232. Mixtures of distributions: Inference and estimation
233. Reparameterization strategies for hidden Markov models and Bayesian approaches to maximum likelihood estimation
234. Parameter estimation for Markov modulated Poisson processes
235. Consistency asymptotically normal parameter estimates for hidden Markov models
236. An EM algorithm for estimation in Markov-modulated Poisson processes
237. Consistent and asymptotically normal parameter estimates for Markov modulated Poisson processes
238. Estimating the order of hidden Markov models
239. On identifiability and order of continuous-time aggregated Markov chains, Markov-modulated Poisson processes, and phase-type distributions
240. On recursive estimation for hidden Markov models
241. Computational Bayesian analysis of hidden Markov models
242. Asymptotically efficient recursive estimation for incomplete data models using the observed information
243. Stylized facts of dally returns series and the hidden Markov model
244. Global convergence and empirical consistency of the generalized Lloyd algorithm
245. A hidden Markov model for rainfall using breakpoint data
246. Modulo-2π phase sequence estimation
247. Estimating the dimension of a model
248. Stochastic processes in estimation theory
249. Recursive estimation from discrete-time point processes
250. A mathematical theory of communication
251. Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy
252. An approach to time series smoothing and forecasting using the EM algorithm
253. Hidden Markov models for fault detection in dynamic systems
254. Markov monitoring with unknown states
255. Frequency line tracking using hidden Markov models
256. Identifiability of mixtures of product measures
257. Heart signal recognition by hidden Markov models - The ECG case
258. Comments on 'application of the conditional population-mixture model to image segmentation'
259. Recursive parameter estimation using incomplete data
260. MAP symbol decoding in channels with error bursts
261. Hidden Markov chains in generalized linear models
262. Identification of hidden Markov models for ion channel currents - Part I: Colored background noise
263. Identification of hidden Markov models for ion channel currents - Part II: State-dependent excess noise
264. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
265. Optimal sequential probability assignment for individual sequences
266. Sequential algorithms for parameter estimation based on the Kullback-Leibler information measure
267. Explicit time correlation in hidden Markov models for speech recognition
268. Cartesian hidden Markov models with applications
269. Lumpable hidden Markov models - Model reduction and reduced complexity filtering
270. Some applications of stochastic differential equations to optimal nonlinear filtering
271. On the convergence properties of the EM algorithm
272. Rotation and Gray-scale transform-invariant texture classification using spiral resampling, subband decomposition, and hidden Markov models
273. The rate-distortion function for source coding with side information at the decoder
274. Some asymptotic properties of the entropy of a stationary ergodic data source with applications to data compression
275. Multiple target tracking and multiple frequency line tracking using hidden Markov models
276. Multiple frequency line tracking with hidden Markov models - Further results
277. Frequency-wavenumber tracking using hidden Markov models
278. Estimation of noisy telegraph processes: Nonlinear filtering versus nonlinear smoothing
279. Exact filters for the estimation of the number of transitions of finite-state continuous-time Markov processes
280. When is the generalized likelihood ratio test optimal?
281. Compression of individual sequences via variable-rate coding
282. Universal decoding for finite-state channels
283. On classification with empirically observed statistics and universal data compression
284. Compression, tests for randomness, and estimating the statistical model of an individual sequence
285. Estimating the number of states of a finite-state source
286. A hidden Markov model for space-time precipitation