A pdf regarding, reading of bar codes from mobile phones. All types of bar codes can be read from the mobile phones. It includes the details regarding, how to convert the bar codes into appropriate formats and then to verify it for the geniality.
PCI ExpressTM Architecture
Add-in Card Compliance Checklist for the PCI Express Base 1.0a SpecificationThe PCI Special Interest Group disclaims all warranties and liability for the use of this document and the information contained herein and assumes no responsibility for any errors that may appear in this document, nor does the PCI Special Interest Group make a commitment to update the information contained herein.Contact the PCI Special Interest Group office to obtain the latest revision of this checklistQuestions regarding the ths document or membership in the PCI Special Interest Group may be forwarded tPCI Special Interest Group5440 SW Westgate Drive #217Portland, OR 97221Phone: 503-291-2569Fax: 503-297-1090 DISCLAIMERThis document is provided "as is" with no warranties whatsoever, including any warranty of merchantability, noninfringement, fitness for any particular purpose, or any warranty otherwise arising out of any proposal, specification, or sample. The PCI SIG disclaims all liability for infringement of proprietary rights, relating to use of information in this specification. No license, express or implied, by estoppel or otherwise, to any intellectual property rights is granted herein.
自適應(Adaptive)神經網絡源程序
The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring
different adaptation algorithms.~..~
There are 11 blocks that implement basically these 5 kinds of neural networks:
1) Adaptive Linear Network (ADALINE)
2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA)
3) Radial Basis Functions (RBF) Networks
4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN)
5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm
A simulink example regarding the approximation of a scalar nonlinear function of 4 variables
Description: C4.5Rule-PANE is a rule learning method which could generate accurate and comprehensible symbolic rules, through regarding a neural network ensemble as a pre-process of a rule inducer.
Reference: Z.-H. Zhou and Y. Jiang. Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. IEEE Transactions on Information Technology in Biomedicine, 2003, vol.7, no.1, pp.37-42.
使用神經網絡集成方法診斷糖尿病,肝炎,乳腺癌癥的案例研究.
The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring
different adaptation algorithms.~..~
There are 11 blocks that implement basically these 5 kinds of neural networks:
1) Adaptive Linear Network (ADALINE)
2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA)
3) Radial Basis Functions (RBF) Networks
4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN)
5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm
A simulink example regarding the approximation of a scalar nonlinear function of 4 variables is included
NXP示例編碼集,Software that is described herein is for illustrative purposes only which
provides customers with programming information regarding the products.
This software is supplied "AS IS" without any warranties. NXP Semiconductors
assumes no responsibility or liability for the use of the software, conveys no
license or title under any patent, copyright, or mask work right to the
product. NXP Semiconductors reserves the right to make changes in the
software without notification. NXP Semiconductors also make no representation
or warranty that such application will be suitable for the specified use without
further testing or modification.
Verilog and VHDL狀態機設計，英文pdf格式
State machine design techniques for Verilog and VHDL
Abstract : Designing a synchronous finite state Another way of organizing a state machine (FSM) is a common task for a digital logic only one logic block as shown in
engineer. This paper will discuss a variety of issues regarding FSM design using Synopsys Design Compiler . Verilog and VHDL coding styles will be 2.0 Basic HDL coding
presented. Different methodologies will be compared using real-world examples.
THIS DESIGN IS PROVIDED TO YOU "AS IS". XILINX MAKES AND YOU RECEIVE NO WARRANTIES OR CONDITIONS, EXPRESS, IMPLIED, STATUTORY OR OTHERWISE, AND XILINX SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTIES OF MERCHANTABILITY, NON-INFRINGEMENT, OR FITNESS FOR A PARTICULAR PURPOSE. This design has not been verified on hardware (as opposed to simulations), and it should be used only as an example design, not as a fully functional core. XILINX does not warrant the performance, functionality, or operation of this Design will meet your requirements, or that the operation of the Design will be uninterrupted or error free, or that defects in the Design will be corrected. Furthermore, XILINX does not warrant or make any representations regarding use or the results of the use of the Design in terms of correctness, accuracy, reliability or otherwise.
