the calculator s usage! after you have inputed 2 operators,choose + - * / function! But the only situation I did t deal with is that when you choos + fuction ,and the operaters signs is like this -A+B,just turn it to B-A!
標簽： calculator the operators function
上傳時間： 2016-02-12
上傳用戶：lili123
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.
標簽： OS-II compatible important Probably
上傳時間： 2013-12-02
上傳用戶：jkhjkh1982
On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標簽： demonstrates sequential Selection Bayesian
上傳時間： 2016-04-07
上傳用戶：lindor
Swfdec still is development software, but has also followed a rigid no-crashes-allowed policy. I believe it s stable enough now to be installed as a default plugin for people that can live with occasional crashes of their browser. But don t blame me if it does crash. File a bug at https://bugs.freedesktop.org/enter_bug.cgi?product=swfdec
標簽： no-crashes-allowed development followed software
上傳時間： 2016-04-14
上傳用戶：franktu
This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標簽： sequential reversible algorithm nstrates
上傳時間： 2014-01-18
上傳用戶：康郎
本人編寫的incremental 隨機神經元網絡算法，該算法最大的特點是可以保證approximation特性，而且速度快效果不錯，可以作為學術上的比較和分析。目前只適合benchmark的regression問題。 具體效果可參考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006.
標簽： incremental 編寫 神經元網絡 算法
上傳時間： 2016-09-18
上傳用戶：litianchu
Thinking in Java, 3rd ed. Revision 4.0 Preface Introduction 1: Introduction to Objects 2: Everything is an Object 3: Controlling Program Flow 4: Initialization & Cleanup 5: Hiding the Implementation 6: Reusing Classes 7: Polymorphism 8: Interfaces & Inner Classes 9: Error Handling with Exceptions 10: Detecting Types 11: Collections of Objects 12: The Java I/O System 13: Concurrency 14: Creating Windows & Applets 15: Discovering Problems 16: Analysis and Design A: Passing & Returning Objects B: Java Programming Guidelines C: Supplements D: Resources Index
標簽： Introduction Thinking Revision Preface
上傳時間： 2014-07-13
上傳用戶：netwolf
The XC226x derivatives are high-performance members of the Infineon XC2000 Family of full-feature single-chip CMOS microcontrollers. These devices extend the functionality and performance of the C166 Family in terms of instructions (MAC unit), peripherals, and speed. They combine high CPU performance (up to 80 million instructions per second) with extended peripheral functionality and enhanced IO capabilities. Optimized peripherals can be adapted flexibly to meet the application requirements. These derivatives utilize clock generation via PLL and internal or external clock sources. Onchip memory modules include program Flash, program RAM, and data RAM.
標簽： high-performance full-feature derivatives Infineon
上傳時間： 2016-12-12
上傳用戶：wab1981
The W3C DOM Core interfaces defines a minimal set of: A. interfaces for accessing and manipulating document objects B. Java object implementations for use with XML parsers. C. Conventions and processes for creating live HTML pages. D. Mutable document
標簽： interfaces A. manipulating accessing
上傳時間： 2017-01-24
上傳用戶：edisonfather
We analyze, both analytically and numerically, the effectiveness of cloaking an infinite cylinder from observations by electromagnetic waves in three dimensions. We show that, as truncated approximations of the ideal permittivity and permeability tensors tend towards the singular ideal cloaking fields, so that the anisotropy ratio tends to infinity, the D and B fields blow up near the cloaking surface. Since the metamaterials used to implement cloaking are based on effective medium theory, the resulting large variation in D and B will pose a challenge to the suitability of the field averaged characterization of " and 碌. We also consider cloaking with and without the SHS (softand- hard surface) lining, shown in [6] to be theoretically necessary for cloaking in the cylindrical geometry. We demonstrate numerically that cloaking is significantly improved by the SHS lining, with both the far field of the scattered wave significantly reduced and the blow up of D and B prevented.
標簽： effectiveness analytically numerically cloaking
上傳時間： 2017-03-30
上傳用戶：zxc23456789
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