In this paper, we present a multiple stage vector quantization technique which allows easy expansion of the original vector quantizer design to operate at higher bit rates for lower distor-tion. The computation and storage reduction is achieved by the fact that the overall requirements are the sum of the requirenierts of each stage ins-tead of an exponentially increasing function of the bit rate as in the original one stage design. In the case of Euclidean distance measures such as the log area ratio measure, experimental re— suits show that the quantizer performance is very close to a theoretically predicted asymptotically optimal rate distortion relationship. I
We study topics in source coding, and vector quantization (VQ) in particular. We approach VQ from tw...
This thesis will examine a Vector Quantization-based system for speech enhancement. Key areas in thi...
We study topics in source coding, and vector quantization (VQ) in particular. We approach VQ from tw...
This dissertation focuses on different quantization methods in speech coding. Variable rate quantiza...
Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Cod...
This dissertation focuses on different quantization methods in speech coding.<p /> <I>Variable rate ...
The objective of the proposed research is to compress data such as speech, audio, and images using a...
The authors present a novel multiple-stage vector-quantization method that allows the adaptation of ...
The authors present a novel multiple-stage vector-quantization method that allows the adaptation of ...
This paper discusses preliminary results of ongoing research to utilize vector quantization to achie...
During the past ten years Vector Quantization (VQ) has developed from a theoretical possibility prom...
Transmission and storage of speech require an efficient representation of the speech signal. The con...
Transmission and storage of speech require an efficient representation of the speech signal. The con...
A new idea for waveform coding using vector quantisation (VQ) is introduced. This idea makes it poss...
ABSTRACT- Performance of conventtonal vector quanttzers tm-proves as the rate and/or dtmenston are I...
We study topics in source coding, and vector quantization (VQ) in particular. We approach VQ from tw...
This thesis will examine a Vector Quantization-based system for speech enhancement. Key areas in thi...
We study topics in source coding, and vector quantization (VQ) in particular. We approach VQ from tw...
This dissertation focuses on different quantization methods in speech coding. Variable rate quantiza...
Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Cod...
This dissertation focuses on different quantization methods in speech coding.<p /> <I>Variable rate ...
The objective of the proposed research is to compress data such as speech, audio, and images using a...
The authors present a novel multiple-stage vector-quantization method that allows the adaptation of ...
The authors present a novel multiple-stage vector-quantization method that allows the adaptation of ...
This paper discusses preliminary results of ongoing research to utilize vector quantization to achie...
During the past ten years Vector Quantization (VQ) has developed from a theoretical possibility prom...
Transmission and storage of speech require an efficient representation of the speech signal. The con...
Transmission and storage of speech require an efficient representation of the speech signal. The con...
A new idea for waveform coding using vector quantisation (VQ) is introduced. This idea makes it poss...
ABSTRACT- Performance of conventtonal vector quanttzers tm-proves as the rate and/or dtmenston are I...
We study topics in source coding, and vector quantization (VQ) in particular. We approach VQ from tw...
This thesis will examine a Vector Quantization-based system for speech enhancement. Key areas in thi...
We study topics in source coding, and vector quantization (VQ) in particular. We approach VQ from tw...