GNU Octave is a high-level language, primarily intended for numerical
computations. It provides a convenient command line interface for
solving linear and nonlinear problems numerically.
The tca package is a Matlab program that implements the tree-dependent
component analysis (TCA) algorithms that extends the independent
component analysis (ICA), where instead of looking for a linear transform
that makes the data components independent, we are looking for components
that can be bes ...
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the ...
英文版G.729语音压缩标准。
GENERAL ASPECTS OF DIGITAL TRANSMISSION
SYSTEMS
CODING OF SPEECH AT 8 kbit/s
USING CONJUGATE-STRUCTURE
ALGEBRAIC-CODE-EXCITED
LINEAR-PREDICTION (CS-ACELP)
The inverse of the gradient function. I ve provided versions that work on 1-d vectors, or 2-d or 3-d arrays. In the 1-d case I offer 5 different methods, from cumtrapz, and an integrated cubic spline, plus several finite difference methods.
In higher dimensions, only a finite difference/linear alge ...
MATLAB Code for Optimal Quincunx Filter
Bank Design
Yi Chen
July 17, 2006
This file introduces the MATLAB code that implements the two algorithms (i.e., Algorithms
1 and 2 in [1], or Algorithms 4.1 and 4.2 in [2]) used for the construction of
quincunx filter banks with perfect reconstruction, linear ...
measure through
the cross-entropy of test data. In addition,
we introduce two novel smoothing techniques,
one a variation of Jelinek-Mercer
smoothing and one a very simple linear interpolation
technique, both of which outperform
existing methods.
Batch version of the back-propagation algorithm.
％ Given a set of corresponding input-output pairs and an initial network
％ [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the
％ network with backpropagation.
％
％ The activation functions must be either linear or tanh. The network
...
％ Train a two layer neural network with the Levenberg-Marquardt
％ method.
％
％ If desired, it is possible to use regularization by
％ weight decay. Also pruned (ie. not fully connected) networks can
％ be trained.
％
％ Given a set of corresponding input-output pairs and an initial
％ network,
％ ...
