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- Stanley C. Ahalt, Ashok K. Krishnamurthy, Prakoon Chen, Douglas E. Melton
- Neural Networks
- 1990

- Adriana Dapena, Stanley C. Ahalt
- IEEE Trans. Circuits Syst. Video Techn.
- 2002

- Aristides S. Galanopoulos, Stanley C. Ahalt
- IEEE Trans. Neural Networks
- 1996

We study the codeword distribution for a conscience-type competitive learning algorithm, frequency sensitive competitive learning (FSCL), using one-dimensional input data. We prove that the asymptotic codeword density in the limit of large number of codewords is given by a power law of the form Q(x)=C.P(x)(alpha), where P(x) is the input data density and… (More)

This study evaluates the performance of the multilayer-perceptron and the frequency-sensitive competitive learning network in identifying five commercial aircraft from radar backscatter measurements. The performance of the neural network classifiers is compared with that of the nearest-neighbor and maximum-likelihood classifiers. Our results indicate that… (More)

- James E. Fowler, Stanley C. Ahalt
- Data Compression Conference
- 1997

In this paper, we describe a new adaptive vector quantization (AVQ) algorithm designed for the coding of nonstationary sources. This new algorithm, generalized threshold replenishment (GTR), diiers from prior AVQ algorithms in that it features an explicit, online consideration of both rate and distortion. Rate-distortion cost criteria are used in both the… (More)

- Daniel F. Stewart, Lee C. Potter, Stanley C. Ahalt
- IEEE Trans. Signal Processing
- 1995

- Jeremy Kepner, Stanley C. Ahalt
- J. Parallel Distrib. Comput.
- 2004

The true costs of high performance computing are currently dominated by software. Addressing these costs requires shifting to high productivity languages such as Matlab. MatlabMPI is a Matlab implementation of the Message Passing Interface (MPI) standard and allows any Matlab program to exploit multiple processors. MatlabMPI currently implements the basic… (More)

We describe hardware that has been built to compress video in real time using full-search vector quantization (VQ). This architecture implements a diierential-vector-quantization (DVQ) algorithm which features entropy-biased codebooks designed using an artiicial neural network (ANN). A special-purpose digital associative memory, the VAMPIRE chip, performs… (More)

In nature, quadrupedal mammals can run at high speeds over uneven terrain, turn sharply, jump obstacles, and stop suddenly. While these abilities are common features in biological locomotion, they represent remarkable feats from both an engineering and control perspective. Although some robots over the past several decades have been capable of dynamic… (More)

- Ashok K. Krishnamurthy, Stanley C. Ahalt, Douglas E. Melton, Prakoon Chen
- IEEE Journal on Selected Areas in Communications
- 1990