msvq
Functions
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int main(int argc, char *argv[])
msvq [ option ] [ infile ]
-l int
length of vector \((1 \le M + 1)\)
-m int
order of vector \((0 \le M)\)
-s str
codebook file
infile str
double-type vector to be quantized
stdout
int-type codebook index
The below example quantizes and reconstructs vectors in
data.d.msvq -s cbfile < data.d | imsvq -s cbfile > data.q
- Parameters:
argc – [in] Number of arguments.
argv – [in] Argument vector.
- Returns:
0 on success, 1 on failure.
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class MultistageVectorQuantization
Perform multistage vector quantization.
The input is the \(M\)-th order vector:
\[ \begin{array}{cccc} x(0), & x(1), & \ldots, & x(M), \end{array} \]and the \(M\)-th order \(N \times I\) codebook vectors, \(\left\{ c_i^{(n)}(m) \right\}\). The output is the \(N\) codebook indices:\[ \begin{array}{cccc} i(1), & i(2), & \ldots, & i(N), \end{array} \]where\[ i(n) = \mathop{\mathrm{argmin}}_j \sum_{j=0}^{I-1} \sum_{m=0}^M (e^{(n)}(m) - c_j^{(n)}(m))^2, \]and the quantization error is\[\begin{split} e^{(n)}(m) = \left\{ \begin{array}{ll} x(m), & n = 1 \\ e^{(n-1)}(m) - c_j^{(n-1)}(m). & n > 1 \\ \end{array} \right. \end{split}\]Public Functions
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MultistageVectorQuantization(int num_order, int num_stage)
- Parameters:
num_order – [in] Order of vector, \(M\).
num_stage – [in] Number of quantization stages, \(N\).
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inline int GetNumOrder() const
- Returns:
Order of vector.
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inline int GetNumStage() const
- Returns:
Number of stages.
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inline bool IsValid() const
- Returns:
True if this object is valid.
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bool Run(const std::vector<double> &input_vector, const std::vector<std::vector<std::vector<double>>> &codebook_vectors, std::vector<int> *codebook_indices, MultistageVectorQuantization::Buffer *buffer) const
- Parameters:
input_vector – [in] \(M\)-th order input vector.
codebook_vectors – [in] \(M\)-th order \(I\) codebook vectors. The shape is \([N, I, M+1]\).
codebook_indices – [out] \(N\) codebook indices.
buffer – [out] Buffer.
- Returns:
True on success, false on failure.
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class Buffer
Buffer for MultistageVectorQuantization class.
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MultistageVectorQuantization(int num_order, int num_stage)
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class VectorQuantization
Perform vector quantization.
The input is the \(M\)-th order vector:
\[ \begin{array}{cccc} x(0), & x(1), & \ldots, & x(M), \end{array} \]and the \(M\)-th order codebook vectors:\[ \begin{array}{cccc} \boldsymbol{c}_0, & \boldsymbol{c}_1, & \ldots, & \boldsymbol{c}_{I-1}. \end{array} \]The output is the index of the codebook vector that minimizes the distance between the input vector and the codebook vector in an Euclidean sense:\[ \mathop{\mathrm{argmin}}_i \sum_{i=0}^{I-1} \sum_{m=0}^M (x(m) - c_i(m))^2. \]Public Functions
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explicit VectorQuantization(int num_order)
- Parameters:
num_order – [in] Order of vector, \(M\).
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inline int GetNumOrder() const
- Returns:
Order of vector.
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inline bool IsValid() const
- Returns:
True if this object is valid.
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bool Run(const std::vector<double> &input_vector, const std::vector<std::vector<double>> &codebook_vectors, int *codebook_index) const
- Parameters:
input_vector – [in] \(M\)-th order input vector.
codebook_vectors – [in] \(M\)-th order \(I\) codebook vectors. The shape is \([I, M+1]\).
codebook_index – [out] Codebook index.
- Returns:
True on success, false on failure.
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explicit VectorQuantization(int num_order)