多階段決策過程（ multistep decision process ）是指 這樣一類特殊的活動(dòng)過程，過程可以按時(shí)間順序分解成若干個(gè)相互聯(lián)系的階段，在每一個(gè)階段都需要做出決策，全部過程的決策是一個(gè)決策序列。 動(dòng)態(tài)規(guī)劃 （ dynamic programming ）算法 是解決 多階段決策過程最優(yōu)化問題 的一種常用方法，難度比較大，技巧性也很強(qiáng)。利用動(dòng)態(tài)規(guī)劃算法，可以優(yōu)雅而高效地解決很多貪婪算法或分治算法不能解決的問題。動(dòng)態(tài)規(guī)劃算法的基本思想是：將待求解的問題分解成若干個(gè)相互聯(lián)系的子問題，先求解子問題，然后從這些子問題的解得到原問題的解； 對(duì)于重復(fù)出現(xiàn)的子問題，只在第一次遇到的時(shí)候?qū)λM(jìn)行求解，并把答案保存起來，讓以后再次遇到時(shí)直接引用答案，不必重新求解 。動(dòng)態(tài)規(guī)劃算法將問題的解決方案視為一系列決策的結(jié)果，與貪婪算法不同的是，在貪婪算法中，每采用一次貪婪準(zhǔn)則，便做出一個(gè)不可撤回的決策；而在動(dòng)態(tài)規(guī)劃算法中，還要考察每個(gè)最優(yōu)決策序列中是否包含一個(gè)最優(yōu)決策子序列，即問題是否具有最優(yōu)子結(jié)構(gòu)性質(zhì)。
標(biāo)簽： multistep decision process 過程
上傳時(shí)間： 2015-06-09
上傳用戶：caozhizhi
Simulation of RM(1,3), equivalent to the (8,4,4) extended Hamming code. Soft-decision decoding performed by the Green machine
標(biāo)簽： Soft-decision Simulation equivalent decoding
上傳時(shí)間： 2015-07-05
上傳用戶：lindor
making componet all about
標(biāo)簽： componet making about all
上傳時(shí)間： 2013-12-21
上傳用戶：源弋弋
machine learning, accuracy estimation, cross-validation, bootstrap, ID3, decision trees, decision graphs, naive-bayes, decision tables, majority, induction algorithms, classifiers, categorizers, general logic diagrams, instance-based algorithms, discretization, lazy learning, bagging, MineSet.
標(biāo)簽： decision cross-validation estimation bootstrap
上傳時(shí)間： 2015-07-26
上傳用戶：趙云興
Learning and Making Decisions When Costs and Probabilities are Both Unknown
標(biāo)簽： Probabilities Decisions and Learning
上傳時(shí)間： 2014-01-21
上傳用戶：waitingfy
Find a classification error for a given decision surface D and a given set of patterns and targets
標(biāo)簽： given classification and decision
上傳時(shí)間： 2013-12-18
上傳用戶：xinzhch
Hard-decision decoding scheme Codeword length (n) : 31 symbols. Message length (k) : 19 symbols. Error correction capability (t) : 6 symbols One symbol represents 5 bit. Uses GF(2^5) with primitive polynomial p(x) = X^5 X^2 + 1 Generator polynomial, g(x) = a^15 a^21*X + a^6*X^2 + a^15*X^3 + a^25*X^4 + a^17*X^5 + a^18*X^6 + a^30*X^7 + a^20*X^8 + a^23*X^9 + a^27*X^10 + a^24*X^11 + X^12. Note: a = alpha, primitive element in GF(2^5) and a^i is root of g(x) for i = 19, 20, ..., 30. Uses Verilog description with synthesizable RTL modelling. Consists of 5 main blocks: SC (Syndrome Computation), KES (Key Equation Solver), CSEE (Chien Search and Error Evaluator), Controller and FIFO Register.
標(biāo)簽： symbols length Hard-decision Codeword
上傳時(shí)間： 2014-07-08
上傳用戶：曹云鵬
一個(gè)由Mike Gashler完成的機(jī)器學(xué)習(xí)方面的includes neural net, naive bayesian classifier, decision tree, KNN, a genetic algorithm, and some manifold learning algorithms.
標(biāo)簽： classifier includes bayesian decision
上傳時(shí)間： 2015-09-11
上傳用戶：gaome
This code was used for making the practical measurements in section 2.3 of my thesis. This Matlab code allows an OFDM signal to be generated based on an input data file. The data can be random data, a grey scale image, a wave file, or any type of file. The generated OFDM signal is stored as a windows wave file, allowing it to be viewed, listened to and manipulated in other programs. The modified wave file can then be decoded by the receiver software to extract the original data. This code was developed for the experiments that I performed in my honours thesis, and thus has not been fully debugged. This is the original code developed for the thesis and so has several problems with it. The BER performance given by the simulations is infact Symbol Error Rate.
標(biāo)簽： This measurements practical section
上傳時(shí)間： 2015-09-20
上傳用戶：tedo811
Making.Use.of.Javascript 關(guān)于Javascript的一本非常好的參考書！
標(biāo)簽： Javascript Making Use of
上傳時(shí)間： 2014-01-26
上傳用戶：hewenzhi
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