### (Table 2). 2.3.2 Hidden Markov Model (HMM)

"... In PAGE 5: ....3.1 Video Analysis The video analysis was performed by two expert surgeons encoding the video of each step of the surgical procedure frame by frame (NTSC - 30 frames per second). The encoding process used a code-book of 14 different discrete tool maneuvers in which the endoscopic tool was interacting with the tissue (Table2 ). Each identified surgical tool/tissue interaction, had a unique F/T pattern.... In PAGE 8: ... 1b. (a) Forces (b) Torques Studying the magnitudes of F/T applied by R1 and ES during each step of the MIS procedures for the different tool/tissue interactions (Table2 ) using the grand median analysis showed that the F/T magnitudes applied by these groups were significantly different (p lt;0.05) and task dependent (Fig.... ..."

### Table 1 State Transition Matrix for a Hidden Markov Model

"... In PAGE 25: ...alues such as Sunny = 1.0, Rainy = 0, and Foggy = 0. 2. A state transition matrix ( Table1 ) that stores the probability of going from one state to another. For example, the first row gives the probability of a sunny day following a sunny day, a rainy day following a sunny day, a foggy day following a sunny day, and so on.... ..."

### Table 2. Accuracy of Hidden Markov Models to recognize haptic gestures

### Table 3: Results of 3 classes segmentation based on hidden Markov models.

"... In PAGE 6: ... Two successive frames will be shifted of 512 samples. Table3 shows results of 3 classes segmentation. Quality rates are better than with simple approaches reviewed in previous section.... ..."

### Table 1: Random elds and their applications

"... In PAGE 6: ..., 1994): E(L)E(S) = E(jAz(T; C)j) = jCjFT (?z); (4) where FT ( ) is the cumulative density function for the marginal distribution of T , and j j is Lebesgue measure. 4 Results The following table summarizes references for the distributions of the two test statistics for random elds in Table1 , except for the Wilk apos;s eld, for which results are still unknown. The distribution Smax for the Hotelling apos;s T 2 eld is also not yet derived.... ..."

### Table 5.1: Cross-entropies for Hidden Markov Models treating the melody notes as observed events and the harmonic symbols as hidden states

### Table 2a. Hidden Markov recurrence probabilities and event matrices: Nonwar Crises

"... In PAGE 18: ... This is presumably due to the fact that various combinations of recurrence probabilities and observed symbol probabilities can produce almost identical likelihoods for the training sequences. Results Discriminating BCOW War and Nonwar Crises The HMMs estimated from the nonwar and war BCOW crises (translated into WEIS codes) are reported in Table2 and Figure 3; Table 2 also reports the events in the transition vectors that have relatively high probabilities. The matrices are quite plausible, as are the differences between them; both models generated large recurrence probabilities on all six states.... In PAGE 21: ...Page 19 Table2 b. Hidden Markov recurrence probabilities and event matrices: War Crises A B C D E Abs recurrence probability 0.... ..."

### Table 1. Observations of a Hidden Markov Model for a meeting of 4 individuals

2005

"... In PAGE 2: ... One observation is a vector containing a binary value (speaking, not speaking) for each individual that is recorded. This vector is transformed to a 1-dimensional discrete code used as input for the HMM (see Table1 ). The automatic speech detector has a sampling rate of 62.... ..."

Cited by 5

### Table I. Performances of SignalP in the neural network (NN) and hidden Markov model (HMM) versions

in Review