μC/OS-II Goals Probably the most important goal of μC/OS-II was to make it backward compatible with μC/OS (at least from an application’s standpoint). A μC/OS port might need to be modified to work with μC/OS-II but at least, the application code should require only minor changes (if any). Also, because μC/OS-II is based on the same core as μC/OS, it is just as reliable. I added conditional compilation to allow you to further reduce the amount of RAM (i.e. data space) needed by μC/OS-II. This is especially useful when you have resource limited products. I also added the feature described in the previous section and cleaned up the code. Where the book is concerned, I wanted to clarify some of the concepts described in the first edition and provide additional explanations about how μC/OS-II works. I had numerous requests about doing a chapter on how to port μC/OS and thus, such a chapter has been included in this book for μC/OS-II.
標(biāo)簽： OS-II compatible important Probably
上傳時間： 2013-12-02
上傳用戶：jkhjkh1982
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 class, the changing decision boundary will be displayed.
標(biāo)簽： calculation Tutorial Discrete Decision
上傳時間： 2013-12-22
上傳用戶：hxy200501
Free 8051 asm compiler for win new host platforms: Win32 and Linux macro processing dramatically improved conditional assembly output in Intel-HEX or OMF-51 format 37 new MCU files documentation in both ASCII and HTML format numberless small extensions and improvements bug fixes For details see the ASEM-51 Release Notes.
標(biāo)簽： dramaticall processing platforms compiler
上傳時間： 2013-12-20
上傳用戶：chongcongying
Free 8051 asm compiler for linux new host platforms: Win32 and Linux macro processing dramatically improved conditional assembly output in Intel-HEX or OMF-51 format 37 new MCU files documentation in both ASCII and HTML format numberless small extensions and improvements bug fixes For details see the ASEM-51 Release Notes.
標(biāo)簽： processing dramatica platforms compiler
上傳時間： 2014-10-28
上傳用戶：wxhwjf
The BNL toolbox is a set of Matlab functions for defining and estimating the parameters of a Bayesian network for discrete variables in which the conditional probability tables are specified by logistic regression models. Logistic regression can be used to incorporate restrictions on the conditional probabilities and to account for the effect of covariates. Nominal variables are modeled with multinomial logistic regression, whereas the category probabilities of ordered variables are modeled through a cumulative or adjacent-categories response function. Variables can be observed, partially observed, or hidden.
標(biāo)簽： estimating parameters functions defining
上傳時間： 2014-12-05
上傳用戶：天誠24
使用matlab實現(xiàn)gibbs抽樣，MCMC: The Gibbs Sampler 多元高斯分布的邊緣概率和條件概率 Marginal and conditional distributions of multivariate normal distribution
上傳時間： 2019-12-10
上傳用戶：real_
Power PCB如何在不同層去設(shè)不同線寬之走線1.選擇 Setup\Design Rules2.選澤 conditional Rules Setup3.設(shè)定Sousce rule object（可依照不同的狀況去選擇使用Al/Classes/Nets/Groups/Pin pairs）4.設(shè)定Against rule object（可依照不同的狀況去選擇使用 Layer/Classes/Nets）5.設(shè)定Existing rule sets將 Sousce rule object與Against rule object之定按Create產(chǎn)生）6.案例說明一有一條信號CLK_32M當(dāng)走到Layer1時需為線寬6mil間距6mil；Layer3時需為線寬20mil間距20mil
標(biāo)簽： padslayout
上傳時間： 2022-07-24
上傳用戶：
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