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One of the most important issues affecting the implementation of microcontroller software deals with the data-decision algorithm. Data-decision refers to decoding the DIO-pin from the CC400/CC900. Two main principles exist for decoding Manchester-coded data: Data decision based on timing the period ...

LVQ学习矢量化算法源程序 This directory contains code implementing the Learning vector quantization network. Source code may be found in LVQ.CPP. Sample training data is found in LVQ1.PAT. Sample test data is found in LVQTEST1.TST and LVQTEST2.TST. The LVQ program accepts input consisting of vectors ...

bayeserr - Computes the Bayesian risk for optimal classifier. ％ bayescln - Classifier based on Bayes decision rule for Gaussians. ％ bayesnd - Discrim. function, dichotomy, max aposteriori probability. ％ bhattach - Bhattacharya s upper limit of mean class. error. ％ pbayescln - Plots discriminat f ...

matlab数据挖掘算法。实用cart决策树进行分类，可识别多类。decision tree algorithm, classification.

The source code for this package is located in src/gov/nist/sip/proxy. The proxy is a pure JAIN-SIP application: it does not need proprietary nist-sip classes in addition of those defined in JAIN-SIP 1.1, you can substitute the NIST-SIP stack by another JAIN-SIP-1.1 compliant stack and it should int ...

ITU-T G.729语音压缩算法。 description: Fixed-point description of commendation G.729 with ANNEX B Coding of Speech at 8 kbit/s using Conjugate-Structure Algebraic-Code-Excited Linear-Prediction (CS-ACELP) with Voice Activity Decision(VAD), Discontinuous Transmission(DTX), and Comfort Noise Generatio ...

Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others. Serious students are directed to the so ...

This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Output is directed to the sc ...

Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifie ...

Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood s ...