### TABLE 12. The same measurements of the best basis search algorithm for the best wave level transform as in table 11 using the Vaidyanathan24 instead of the Daubechies8 filter.

### TABLE 11. The number of times each decomposition level was chosen by the best basis search algorithm of the best wave level transform. The left number corresponds to the 60 transforms with a block length of 2048 and the right number corresponds to the 480 transforms with 256 samples.

### Table 2: Percent error classification. Numbers in brackets represent standard deviations. Wavelet1 uses the first 15 wavelet coefficients of the signal while Wavelet2 stands for a discrimination based on L2 distance of the distributions of the two classes. QDB1 means that first the quadratic discrim- ination best basis is found (see text for details) and then the first 12 or 15 coefficients of this basis are used. In Quadratic2, the discriminating coefficients based on the L2 distance of the distributions of the two classes are found from the same best basis.. In all cases the discrimination is done on each dimension separately.

"... In PAGE 8: ... We have achieved far better results on this frequency band, and thus provide more results to demonstrate the effect of different mother wavelets, different discrimination methods and different number of features. Table2 provides results of the experiments with the wide-band data. The top panel indicates that vast dimensionality reduction is essential for improved performance as the discriminating information is confined in a much smaller dimensional space.... ..."

### Table 1: Wavelet packets decomposition. Coifman and Wickerhauser introduced the best ba- sis algorithm [2], which results in a complete basis called the best basis which minimizes certain informa- tion cost function. Algorithm locally performs com- parison between a parent and the children nodes and helps us to keep the parent node or to \sink quot; deeper toward the children nodes. The entropy of a nonne- gative sequence p, with P pi = 1, was chosen as a popular discriminant measure: H(p) = ? X

"... In PAGE 2: ... Decomposition can be presented as a binary tree structure where nodes of the tree represent subspaces with di erent time-frequency lo- calization characteristics. In Table1 , wavelet packets are represented in a rectangular form. First line de- notes the original signal (a vector in vector space lt;8), while the following lines are calculated by using low (summing - s) and high (di erencing - d) lters.... ..."

### Table 2: Entropies attained by the conventional WPD, sub-optimal SIWPD (d lt;L) and optimal SIWPD (d=L) for acoustic pressure waveforms. The average entropy and the variance are lower when using the SIWPD, and they further decrease when d is larger. Table 1

1997

"... In PAGE 11: ... The number of real multiplications required by these algorithms for expanding a given waveform in its best basis are respectively 2560, 5120, 9216 and 31744. Table2 lists the attained entropies by the best-basis algorithms for an arbitrary subset of ten waveforms. Clearly, the average entropy is lower when using the SIWPD.... ..."

Cited by 27

### Table 1 Comparison of different search algorithms In the table 1, the attributes create a basis for decision making. Each of the algorithms examined in the paper contains weak and strong attributes. It is the function of the problem space to weight the trade-offs between the algorithm and determine which algorithms provides the best solution

"... In PAGE 6: ...igure 12 status information monitoring agent [16] ......................................................................41 List of Tables Table1 Comparison of different search algorithms.... ..."

### Table 1. PSNR(dB) versus bit rate results for DWT and WPT coded images.

"... In PAGE 7: ... The Lagrangian cost function in Equation (1) is used for the best basis selection. The PSNR results are tabulated in Table1 . Some of the WPT encoding results ob- tained by SFQ [9] coder are included for comparison.... ..."

### Table 2: Results for initial fractal block coding in the wavelet domain. Level 2 to Level 1, domain block size 4, no search, basis projection not enabled. Wavelet Rate Value MSE PSNR Bits per Pixel

"... In PAGE 30: ... 5.1 Results Table2 shows the results of using the coder ( with rst range coe cient coder ) with a rate value of 512 and varying the wavelet quantiser rate. Basis projection is not enabled and the coder does no searching for the best range block.... ..."

### Table 5: Number of quot;no-hits quot; and quot;too-many-hits quot; situations for the most successful and least successful subjects.

1996

"... In PAGE 7: ... Enlarging the set of retrieved items is particularly difficult for less successful users. Table5 shows that quot;no-hits quot; situations are much more common for the least successful users (defined as the bottom five subjects ranked on the basis of search effectiveness) than for best ones (the top five ones). quot;no-hits quot; situations are also much more common, for worst subjects, than quot;too-many-hits quot; situations.... ..."

Cited by 45

### Table 5: Number of quot;no-hits quot; and quot;too-many-hits quot; situations for the most successful and least successful subjects.

1996

"... In PAGE 7: ... Enlarging the set of retrieved items is particularly difficult for less successful users. Table5 shows that quot;no-hits quot; situations are much more common for the least successful users (defined as the bottom five subjects ranked on the basis of search effectiveness) than for best ones (the top five ones). quot;no-hits quot; situations are also much more common, for worst subjects, than quot;too-many-hits quot; situations.... ..."

Cited by 45