W.H. Equitz, "A New Vector Quantization Clustering Algorithm," IEEE Trans. Acoust. Speech Signal Proc., pp. 1568-1575, Oct., 1989. Home/Search Document Not in Database Summary Related Articles Check |
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Algorithms for Fast Vector Quantization - Arya, Mount (1993) (24 citations) (Correct)
....sources. Both uncorrelated and correlated sources were used. For the correlated sources, we used 0.9 as the correlation coe#cient. All the sources had zero mean and unit variance. In dimension 16 we used codebooks consisting of 65,536 codevectors generated by the k d tree based Equitz algorithm [13]. We sped up Equitz algorithm in several ways and, for uncorrelated sources, instead of building balanced k d trees as is customary, we partitioned the rectangles corresponding to the internal nodes such that a random number of points were contained in each part. This led to codebooks of better ....
W. H. Equitz. A new vector quantization clustering algorithm. IEEE Transactions on Acoust., Speech and Signal Process., 37(10):1568--1575, October 1989.
Integer Programming Approach to Fixed-rate Entropy-coded .. - Nikneshan, Hons.. (Correct)
....and Information Technology Ontario (CITO) algorithm for the entropy constrained vector quantization (ECVQ) Their implementation is similar to generalized Lloyd algorithm [7] The generalized Lloyd algorithm [7] is a time consuming approach. In order to alleviate this problem, Equitz [8] proposed a recursive algorithm, called pairwise nearest neighbor (PNN) Recently, an entropyconstrained version of the PNN design algorithm was proposed by Garrido, Pearlman, and Finamore [9] and is called entropy constrained pairwise nearest neighbor (ECPNN) All of these methods have a ....
W. H. Equitz, "A new vector quantization clustering algorithm, " IEEE Trans. Acoust., Speech, Signal Process., vol. 37, pp. 1568--1575, Oct. 1989.
Construction of a Shared Secret Key Using Continuous Variables - Cardinal, Van Assche (2003) (Correct)
.... k f k )g until variation of EXA XB jXA k PXB jK ) becomes negligible While this algorithm is an adaptation of the well known generalized Lloyd algorithm, we can consider that the agglomerative information bottleneck technique [28] is an adaptation of the Pairwise Nearest Neighbor algorithm [10] for vector quantizer design. C Practical algorithm The previous description of the local optimization algorithm is rather general and not directly implementable. First, probability distributions are generally estimated up to a certain precision. Then, the design of the improved quantizer is not ....
W. H. EQUITZ, A new vector quantization clustering algorithm, IEEE Trans. Acoust., Speech, Signal Processing, 37 (1989), pp. 1568--1575.
Comparison and Optimization of Methods of Color Image.. - BRAQUELAIRE, BRUN (1997) (2 citations) (Correct)
....have been done to adapt vector quantization techniques [17] of video signal coding. Goldberg [16] experimented the LBG fixed point algorithm [23] as postprocessing for several heuristics [18] 19] 3] and Balasubramian and al. 2] proposed an algorithm based on the PNN algorithm of Equitz [11]. In all these works vector quantization is used to improve clustering heuristic and thus the use of a good color quantization heuristic remains profitable to preprocess the input data. There are few examples [3] of a direct construction of the function Q. Most of the time this construction is ....
William H. Equitz. A new vector quantization clustering algorithm. IEEE transactions on acoustics, speech, and signal processing, 37(10):1568--1575, october 1989.
Lazy Algorithms for Dynamic Closest Pair with Arbitrary.. - Cardinal, Eppstein (2004) (Correct)
....deletions and one insertion. Cluster similarity can be measured in several ways, and such routines should not rely on any assumptions about the similarity measure. It is worth noticing that in the vector quantization literature, this algorithm is known as the Pairwise Nearest Neighbor (PNN) method [5]. An example of PNN like algorithm that uses a more sophisticated distance measure can be found in [3] This is a good example of a practical application that uses distance measures which have no useful geometric properties. It is shown in [4] that most of these algorithms use a brute force search ....
W. H. Equitz. A new vector quantization clustering algorithm. IEEE Trans. Acoust., Speech, Signal Processing, 37(10):1568-1575, October 1989.
Quantization with an Information-Theoretic Distortion Measure - Cardinal (2002) (Correct)
.... . A suitable tie breaking rule is used in the update step for Q k . While this algorithm is an adaptation of the well known generalized Lloyd algorithm, we can consider that the agglomerative information bottleneck technique [11] is an adaptation of the Pairwise Nearest Neighbor algorithm [5] for vector quantizer design. The local optimization algorithm can be implemented in practice using a training set T of outcomes of XA and applying the nearest neighbor rule (8) for each element of the set. The algorithm becomes as described in Algorithm 2. 4 Algorithm 1 A general alternate ....
W. H. Equitz. A new vector quantization clustering algorithm. IEEE Trans. Acoust., Speech, Signal Processing, 37(10):1568-1575, October 1989.
Pattern Clustering Using Incremental Splitting for.. - Chu, Roddick (2001) (Correct)
.... merging. Binary Splitting [3] Start with a single cluster. In each iteration, every cluster is spilt into two smaller ones. Therefore, the number of clusters doubles after each iteration. The Kmeans method is called to refine the clustering in each iteration. Pair wise Nearest Neighbour Merge [4]: Start with M clusters, one cluster for each supplied data item. In each iteration, one pair of nearest neighbours is merged. The K means method is called to refine the clustering in each iteration. 3 Incremental Splitting The general structure discussed in the previous section can be regarded ....
W. H. Equitz, A New Vector Quantization Clustering Algorithm, IEEE Trans. On Acoustics, Speech, and Signal Processing, 37(1989), 1568-1575.
BinClass: A Software Package for Classifying Binary.. - Gyllenberg, Koski, Lund (Correct)
....4.1.2 and 4.1.3. To analyze the uncertainty due to the probabilistic nature of the GLA and LS implementations, a simple tool of statistical analysis is described in section 4.2.3. For comparison we implemented two other traditional methods in BinClass; the Split [17] and Pairwise Nearest Neighbor [48, 17] algorithms. GLA can be incorporated in both of them. Many variations of both methods have been suggested. The idea of the Split algorithm is to start from the trivial classification where k = 1, and all t elements are put in the same class. Then we start splitting one class at the time with some ....
Equitz, W.H.: "A new vector quantization clustering algorithm", IEEE Trans. Acoustics Speech Signal Processing, 1, 1989, 1568-1575.
Control Point Assessment for Image Registration - Fonseca, Kenney (1999) (Correct)
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W.H. Equitz, "A New Vector Quantization Clustering Algorithm," IEEE Trans. Acoust. Speech Signal Proc., pp. 1568-1575, Oct., 1989.
Comparison of Clustering Algorithms in Speaker.. - Kinnunen, Kilpelinen.. (Correct)
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Equitz W.H.: A new vector quantization clustering algorithm, IEEE Trans. on Acoustics, Speech, and Signal Processing, 37(10): 1568-1575, October 1989.
Genetic Algorithms for Large Scale Clustering Problems - Fränti, Kivijärvi.. (1997) (Correct)
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W.H. Equitz, A new vector quantization clustering algorithm. IEEE Transactions on Acoustics, Speech, and Signal Processing, 37, 1568-1575, October 1989.
Practical Methods for Speeding-Up the Pairwise Nearest .. - Virmajoki, Fränti.. (2001) (Correct)
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W. H. Equitz, "A new vector quantization clustering algorithm," IEEE Trans. Acoust., Speech, Signal Process. 37#10#, 1568 --1575 #1989#.
Construction of a Shared Secret Key Using Continuous Variables - Cardinal, Van Assche (2003) (Correct)
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W. H. EQUITZ, A new vector quantization clustering algorithm, IEEE Trans. Acoust., Speech, Signal Processing, 37 (1989), pp. 1568--1575.
Fast Pairwise Nearest Neighbor Based Algorithm for.. - Virmajoki, Fränti (2003) (Correct)
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W. H. Equitz, "A new vector quantization clustering algorithm," IEEE Trans. Acoust., Speech, Signal Process. 37#10#, 1568 --1575 #1989#.
A Fast Exact GLA Based on Code Vector Activity Detection - Kaukoranta, Fränti.. (2000) (Correct)
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W. H. Equitz, "A new vector quantization clustering algorithm," IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 1568--1575, Oct. 1989.
Iterative Split-and-Merge Algorithm for VQ Codebook.. - Kaukoranta, Fränti.. (1998) (Correct)
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W.H. Equitz, "A New Vector Quantization Clustering Algorithm". IEEE Transactions on Acoustics, Speech, and Signal Processing, 37 (10), 15681575, (October 1989).
N-Candidate methods for location invariant dithering of color .. - Lemström, Fränti (2000) (Correct)
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W.H. Equitz, A new vector quantization clustering algorithm, IEEE Transactions on Acoustics, Speech, and Signal Processing 37 (10) (1989) 1568--1575.
Fast and Memory Efficient Implementation of the Exact PNN - Fränti, Kaukoranta, Shen.. (2000) (Correct)
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W. H. Equitz, "A new vector quantization clustering algorithm," IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 1568--1575, Oct. 1989.
Vector Quantization by Lazy Pairwise Nearest Neighbor.. - Kaukoranta, Fränti.. (1999) (Correct)
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W.H. Equitz, "A new vector quantization clustering algorithm", IEEE Transactions on Acoustics, Speech, and Signal Processing 37 (10), pp. 15681575, October 1989.
Binary Vector Quantizer Design Using Soft Centroids - Fränti, Kaukoranta (1999) (Correct)
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W.H. Equitz, A new vector quantization clustering algorithm, IEEE Trans. Acoust. Speech Signal Process. 37 (10) (October 1989) 1568}1575.
Conditional Entropy-Constrained Vector Quantization.. - de Garrido, Pearlman (2001) (1 citation) (Correct)
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W. H. Equitz, "A new vector quantization clustering algorithm", IEEE Trans. on Acoustics, Speech and Signal Processing, vol. ASSP-37, pp. 1568--1575, Oct. 1989.
Scalar Chrominance And Its Applications In Color Representation - Bartkowiak, Domanski (Correct)
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W. H. Equitz, "A new vector quantization clustering algorithm", IEEE Transactions on Acoustics, Speech and Signal Processing, 37, 1568--1575 (1989).
Fast Full-Search Equivalent Nearest-Neighbour Search Algorithms - Chua (1999) (Correct)
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William H. Equitz. A new vector quantization clustering algorithm. IEEE Transactions on Acoustics, Speech, and Signal Processing, 37(10):1568--1575, October 1989.
Lossy Compression of Scientific Data via Wavelets and Vector.. - Goldschneider (1997) (Correct)
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W. H. Equitz. A new vector quantization clustering algorithm. IEEE Transactions on Acoustics Speech and Signal Processing, 37(10):1568--1575, October 1989.
Adaptive compression of DICOM-image data - Hludov, Engel, Meinel (Correct)
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W.H. Equitz. A New Vector Quantization Clustering Algorithm. IEEE Transactions on Acoustics, Speech, and Signal Processing, 37:1568-1575, October 1989.
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