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Bit Allocation and Encoding for Vector Sources
Adrian Segall
Massachusetts Institute of Technology
Research output
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Contribution to journal
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Article
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peer-review
121
Scopus citations
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Dive into the research topics of 'Bit Allocation and Encoding for Vector Sources'. Together they form a unique fingerprint.
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Keyphrases
Coding Scheme
100%
Bit Encoding
100%
Bit Allocation
100%
Vector Sources
100%
Memoryless
33%
Encoder
33%
Minimum Mean Square Error
33%
Optimal Allocation
33%
Noiseless Channels
33%
Rate-distortion
33%
Mean Squared Error
33%
Decorrelating
33%
Entropy Quantization
33%
Efficient Transmission
33%
Engineering
Encoding Scheme
100%
Source Vector
100%
Quantization (Signal Processing)
66%
Transmissions
33%
Mean-Squared-Error
33%
Optimal Allocation
33%
Practical Problem
33%
Mean Square Error
33%
Independent Component
33%
Computer Science
Encoding Scheme
100%
Quantization (Signal Processing)
66%
Noiseless Digital Channel
33%
Optimal Allocation
33%
Independent Component
33%
Mathematics
Encoding Scheme
100%
Memoryless
33%
Total Number
33%
Mean Square Error
33%
Squared Error
33%
Independent Component
33%