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Convolutional(2,1,6) Encoder and soft decision Viterbi Decoder 刚才上载的有错误,已修正

How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-e ...

主要是KNN（the k-nearest neighbor　algorithm ）,LVQ1（learning vector quantization 1）, DSM（decision surface mapping）算法。 and a simple clustering algorithm.

One kind of decision-making tree algorithm, can be seen as one kind data mining algorithm ,find the rule from large-scale data middle.

A general decision rule for stochastic blind maximum-likelihood OSTBC detection is derived.

Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assuming BPSK. Brute force Monte Carlo approach is unsatisfactory (takes too long) to find the BER curve. The computation uses a quasi-analytic (QA) technique that relies on the estimation (approximate on ...

The MDP toolbox proposes functions related to the resolution of discrete-time Markov Decision Process : finite horizon, value iteration, policy iteration, linear programming algorithms with some variants. The functions (m-functions) were developped with MATLAB v6.0 (one of the functions requires th ...

A Web Tutorial on Discrete Features of Bayes Decision Theory This applet allows for the calculation of the decision boundary given a three dimensional feature vector. Specifically, by stipulating the variables such as the priors, and the conditional likelihoods of each feature with respect to each c ...

Bayes Decision Procedure Bases on MATLAB Progame

维特比译码程序。viterbi decoder with hard decision