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matlab例程 THIS M-FILE USES THE TRANFER MATRIX METHOD TO EVALUATE THE COUPLED-MODE %EQUATIONS. THE REFLECTION

THIS M-FILE USES THE TRANFER MATRIX METHOD TO EVALUATE THE COUPLED-MODE %EQUATIONS. THE REFLECTION SPECTRUM OF THE GRATING AND THE TRANSMISSION %SPECTRUM, DELAY AND DISPERSION OF THE FABRY-PEROT FILTER ARE SIMULATED
https://www.eeworm.com/dl/665/182962.html
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数学计算 TRANSFER MATRIX FORMALISM FOR GRATINGS WITH DEFECTS AND GAIN

TRANSFER MATRIX FORMALISM FOR GRATINGS WITH DEFECTS AND GAIN
https://www.eeworm.com/dl/641/182964.html
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其他行业 Matlab codes for random matrix theory.

Matlab codes for random matrix theory.
https://www.eeworm.com/dl/668/186712.html
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其他 Random matrix theory - exercise.

Random matrix theory - exercise.
https://www.eeworm.com/dl/534/186713.html
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其他 Random matrix theory - for communication systems.

Random matrix theory - for communication systems.
https://www.eeworm.com/dl/534/186715.html
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书籍源码 matrix calculation for allocate memory

matrix calculation for allocate memory
https://www.eeworm.com/dl/532/191643.html
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单片机开发 Key matrix scan code for HT48R10

Key matrix scan code for HT48R10
https://www.eeworm.com/dl/648/192377.html
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编辑器/阅读器 给vim增加函数列表。Author: Yegappan Lakshmanan (yegappan AT yahoo DOT com) For Vim version 6.0 and above L

给vim增加函数列表。Author: Yegappan Lakshmanan (yegappan AT yahoo DOT com) For Vim version 6.0 and above Last change: 2006 November 14
https://www.eeworm.com/dl/626/192464.html
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行业发展研究 Knowledge of the process noise covariance matrix is essential for the application of Kalman filteri

Knowledge of the process noise covariance matrix is essential for the application of Kalman filtering. However, it is usually a difficult task to obtain an explicit expression of for large time varying systems. This paper looks at an adaptive Kalman filter method for dynamic harmonic state estimatio ...
https://www.eeworm.com/dl/692/193691.html
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Linux/Unix编程 performs one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A *x + beta*y, w

performs one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A *x + beta*y, where alpha and beta are scalars, x and y are vectors and A is an m by n matrix
https://www.eeworm.com/dl/619/193918.html
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