소스 코딩

처리할 신호의 형식 지정

다양한 소스 코딩을 적용하여 대표 파티션, 특정 코드북 매핑, 압축, 확장, 압신 및 양자화에 따라 신호의 형식을 지정합니다.

함수

`arithdeco`	Decode binary code by arithmetic decoding
`arithenco`	Encode sequence of symbols by arithmetic encoding
`compand`	Source coding mu-law or A-law compressor or expander
`dpcmdeco`	Decode using differential pulse code modulation
`dpcmenco`	Encode using differential pulse code modulation
`dpcmopt`	Optimize differential pulse code modulation parameters
`huffmandeco`	Decode binary code by Huffman decoding
`huffmandict`	Generate Huffman code dictionary for source with known probability model
`huffmanenco`	Encode sequence of symbols by Huffman encoding
`lloyds`	Optimize quantization parameters using Lloyd algorithm
`quantiz`	Produce quantization index and quantized output value

`comm.DifferentialDecoder`	Decode binary signal using differential decoding
`comm.DifferentialEncoder`	Encode binary signal using differential coding

A-Law Compressor	Implement A-law compressor for source coding
A-Law Expander	Implement A-law expander for source coding
Differential Decoder	Decode binary signal using differential coding
Differential Encoder	Encode binary signal using differential coding
Mu-Law Compressor	Implement µ-law compressor for source coding
Mu-Law Expander	Implement µ-law expander for source coding
Quantizing Decoder	Decode quantization index according to codebook
Quantizing Encoder	Quantize signal using partition and codebook

Source Coding
Scalar quantization is a process that maps all inputs within a specified range to a common value.
Quantize and Compand an Exponential Signal
When transmitting signals with a high dynamic range, quantization using equal length intervals can result in loss of precision and signal distortion.
Differential Pulse Code Modulation
Learn about differential pulse code modulation (DPCM) and how it is used as a predictive quantization method.
Quantization
Scalar quantization is a process that maps all inputs within a specified range to a common value.