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VC书籍 Sequential Monte Carlo
Sequential Monte Carlo
其他 program to perform sequential divider in vhdl
program to perform sequential divider in vhdl
数学计算 Algorithm GSP in C for patterns sequential
Algorithm GSP in C for patterns sequential
其他数据库 This is example for E-Market to use sequential file instead of database.
This is example for E-Market to use sequential file instead of database.
VHDL/FPGA/Verilog It is n-bit sequential divider in verilog language
It is n-bit sequential divider in verilog language
Mentor Design Safe Verilog State Machine（Synplicity）
 
One of the strengths of Synplify is the Finite State Machine compiler. This is a powerfulfeature that not only has the ability to automatically detect state machines in the sourcecode, and implement them with either sequential, gray, or one-hot encoding. But alsoperform a reachability ana ...
单片机编程 lpc2478完全使用手册
NXP Semiconductor designed the LPC2400 microcontrollers around a 16-bit/32-bitARM7TDMI-S CPU core with real-time debug interfaces that include both JTAG andembedded Trace. The LPC2400 microcontrollers have 512 kB of on-chip high-speedFlash memory. This Flash memory includes a special 128-bit wide me ...
可编程逻辑 Design Safe Verilog State Machine（Synplicity）
 
One of the strengths of Synplify is the Finite State Machine compiler. This is a powerfulfeature that not only has the ability to automatically detect state machines in the sourcecode, and implement them with either sequential, gray, or one-hot encoding. But alsoperform a reachability ana ...
人工智能/神经网络 最新的支持向量机工具箱
最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, ...
生物技术 This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise
This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal ...