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单片机开发 * The keyboard is assumed to be a matrix having 4 rows by 6 columns. However, this code works for an

* The keyboard is assumed to be a matrix having 4 rows by 6 columns. However, this code works for any * matrix arrangements up to an 8 x 8 matrix. By using from one to three of the column inputs, the driver * can support "SHIFT" keys. These keys are: SHIFT1, SHIFT2 and SHIFT3.
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软件设计/软件工程 Lex helps write programs whose control flow is directed by instances of regular expressions in the

Lex helps write programs whose control flow is directed by instances of regular expressions in the input stream. It is well suited for editor-script type transformations and for segmenting input in preparation for a parsing routine.
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matlab例程 This function can inflexibly used by the programmers who want to find neighbor in som

This function can inflexibly used by the programmers who want to find neighbor in som
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MTK 论MTK平台屏幕切换特效 - 学习交流 - 富贵论坛 - Powered by Discuz!.mh MTK电话薄中所用到的数据结构及其在电话薄中的作用.pdft

论MTK平台屏幕切换特效 - 学习交流 - 富贵论坛 - Powered by Discuz!.mh MTK电话薄中所用到的数据结构及其在电话薄中的作用.pdft
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文章/文档 自制wiggler make wiggler by self,very easy.

自制wiggler make wiggler by self,very easy.
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其他 ecg simulation.developped by Matlab

ecg simulation.developped by Matlab
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微处理器开发 StudyARM Step by Step StudyARM Step by Step

StudyARM Step by Step StudyARM Step by Step
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matlab例程 %For the following 2-class problem determine the decision boundaries %obtained by LMS and perceptro

%For the following 2-class problem determine the decision boundaries %obtained by LMS and perceptron learning laws.
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matlab例程 PRINCIPLE: Removal of the row mean from each row, followed by division of the row by the respective

PRINCIPLE: Removal of the row mean from each row, followed by division of the row by the respective row standard deviation.
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书籍源码 BP neural network for time series analysis predicted that by entering the corresponding time-series

BP neural network for time series analysis predicted that by entering the corresponding time-series data to predict the future, suitable for beginners on the BP neural network learning
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