博世公司定義的CAN（Controller Area Network協(xié)議（ver2.0）
標(biāo)簽： Controller Network Area CAN
上傳時(shí)間： 2015-06-14
上傳用戶：klin3139
This is a program that I did several days ago.It is about Airport Ticket Sale System.You can use it as an example.
標(biāo)簽： Airport program several System
上傳時(shí)間： 2015-06-14
上傳用戶：skhlm
Intro_to_VDSP_transcript.rar is very nice doucoment ,you can use it freely
標(biāo)簽： Intro_to_VDSP_transcript doucoment freely nice
上傳時(shí)間： 2014-01-05
上傳用戶：wfl_yy
Displaying large amounts of technical data in a chart can be a frustrating task. You can find tons of charting controls with fancy effects and useless features, but when it comes to displaying many curves at once, independently scaled on different axes, most of them fail.
標(biāo)簽： frustrating Displaying can technical
上傳時(shí)間： 2014-01-05
上傳用戶：exxxds
JTAG PCB file ,you can make pcb board with this file .
標(biāo)簽： file board JTAG make
上傳時(shí)間： 2014-01-19
上傳用戶：xlcky
a non-sharing smart pointer class that can be used with STL containers such as std::map, vector, list, set, and deque. The smart pointer has an assignment operator and greater than operator that call the target object s operator.
標(biāo)簽： non-sharing containers pointer vector
上傳時(shí)間： 2015-06-15
上傳用戶：Late_Li
annie is an ANN, ie, Artificial Neural Network library developed in C++. It can be used to implement various kinds of neural networks like Multi-Layer Perceptron, Radial basis function networks, Hopfield networks etc.
標(biāo)簽： Artificial developed implement Network
上傳時(shí)間： 2014-08-17
上傳用戶：trepb001
The Hopfield model is a distributed model of an associative memory. Neurons are pixels and can take the values of -1 (off) or +1 (on). The network has stored a certain number of pixel patterns. During a retrieval phase, the network is started with some initial configuration and the network dynamics evolves towards the stored pattern which is closest to the initial configuration.
標(biāo)簽： model distributed associative Hopfield
上傳時(shí)間： 2015-06-17
上傳用戶：l254587896
Single-layer neural networks can be trained using various learning algorithms. The best-known algorithms are the Adaline, Perceptron and Backpropagation algorithms for supervised learning. The first two are specific to single-layer neural networks while the third can be generalized to multi-layer perceptrons.
標(biāo)簽： Single-layer algorithms best-known networks
上傳時(shí)間： 2015-06-17
上傳用戶：趙云興
tms320f2707 控制的 can程序 ISA接口方式 調(diào)試通過(guò)
上傳時(shí)間： 2013-12-19
上傳用戶：ghostparker
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