### Table 4: Performance of the algorithm in presence of various sources of noise in mixtures: Normal- ized mean-squared (NSE) and cross-talk (CTE) errors for image separation, applying our multiscale adaptive approach along with the Natural Gradient based separation.

2003

"... In PAGE 20: ... Therefore, at sufficiently high signal-to-noise energy ratios (SNR), the large coefficients of the signals are only slightly distorted by the noise coefficients. As a result, the presence of noise has a minor effect on the estimation of the unmixing matrix (see the CTE entries in Table4 ). Note, that the NSE entries reflect the noise energy passed to the reconstructed sources from the mixtures.... ..."

Cited by 4

### Table 4: Performance of the algorithm in presence of various sources of noise in mixtures: Normal- ized mean-squared (NSE) and cross-talk (CTE) errors for image separation, applying our multiscale adaptive approach along with the Natural Gradient based separation.

2003

"... In PAGE 20: ... Therefore, at sufficiently high signal-to-noise energy ratios (SNR), the large coefficients of the signals are only slightly distorted by the noise coefficients. As a result, the presence of noise has a minor effect on the estimation of the unmixing matrix (see the CTE entries in Table4 ). Note, that the NSE entries reflect the noise energy passed to the reconstructed sources from the mixtures.... ..."

Cited by 4

### Table 2: 2{D multiscale relaxation algorithm.

1995

"... In PAGE 9: ....g., horizontal, vertical and diagonal bands. While the order in which the horizontal and vertical bands are processed appears arbitrary, the diagonal band is processed last for consistency with the multiresolution approach. The relaxation algorithm is summarized in Table2 . The inter{scale error feedback term (s;j ) j includes terms from scale j + 1 and from all bands at scale j visited prior to .... In PAGE 11: ... perceptually at domain where the unweighted criterion (4) is useful [19], as shown in Fig. 4. The pre lter P has magnitude{squared frequency response approximating W(u; v). The output z of this lter is subband coded using the algorithm in Table2 (unweighted L2 criterion) with identical quantizers in all bands. At the decoder, the post ltered image ^ y is such that ^ EW = kP(y ? ^ yk2 = kz ? ^ zk2 is minimized.... ..."

Cited by 15

### Table 1: Parameters and results of the multi-scale algorithm.

"... In PAGE 9: ...B4CZB5 D6CTCU (in seconds); the number of candidates AC AC CB B4CZB5 AC AC after pruning and merging; and the number AC AC CB B4CZB5 CKCC AC AC of true candidates in that set. Table1 below shows the parameters and results of the test. The minimum length C4 D1CXD2 of candidates to look for was set at 210 pixels (17.... ..."

### Table 1: Parameters and results of the multi-scale algorithm.

"... In PAGE 9: ...D6CTCU (in seconds); the number of candidates AC ACCBB4CZB5AC AC after pruning and merging; and the number AC ACCBB4CZB5 CK CC AC AC of true candidates in that set. Table1 below shows the parameters and results of the test. The minimum length C4D1CXD2 of candidates to look for was set at 210 pixels (17.... ..."

### Table 2: Distribution of execution time between the tasks performed within the multiscale color ratio approach.

2001

"... In PAGE 7: ... Table 1 shows the execution times obtained, where saliency detection with our multiscale color ratio method presents lower execution time than the other approaches. Table2 shows the distribution of computing time between the most important tasks carried out by the proposed algorithm. The computation of center- surround differences is only 8% of the total execution time, because these differences are computed at the scale of the centers, instead of at the source image scale.... ..."

Cited by 1

### Table 6: Number nze of nonzero elements, compression rate cpr, errors ERR e and MERRx for the multiscale algorithm on the cube for level dependent thresholding.

1994

"... In PAGE 20: ... So far we have only made a rst attempt using level dependent thresholds in order to t the quadratic order of convergence. In this case of level dependent thresholding we have observed a small improvement (see Table6 ). Actually we have not invested further e orts in this direction.... ..."

Cited by 22

### Table 1: Adaptive Scheduling Algorithms.

2000

Cited by 64

### Table 1: Adaptive Scheduling Algorithms.

2000

Cited by 64