By Marrone P.
Read Online or Download Java Object Oriented Neural Engine. The Complete Guide PDF
Similar programming: programming languages books
Considering in Java, 3rd variation is the much-anticipated revision of Bruce Eckel's best-selling advent to Java. In pondering in Java, 3/e, Bruce Eckel offers entire integration of JDK 1. four applied sciences to his award successful 'Thinking in' presentation. Eckel introduces all of the fundamentals of gadgets as Java makes use of them, then walks rigorously during the primary options underlying all Java programming -- together with application circulate, initialization and cleanup, implementation hiding, reusing periods, and polymorphism.
C# 2010 for Programmers (4th Edition) (Deitel Developer Series)
Written for programmers with a history in C++, Java or different high-level, object-oriented languages, this publication applies the Deitel signature live-code method of instructing programming and explores Microsoft’s C# 2010 language and . web four intensive. The booklet is up-to-date for visible Studio® 2010 and C# four, and offers C# techniques within the context of totally established courses, whole with syntax shading, special line-by-line code descriptions and software outputs.
- A Byte of Python 1.92
- Dynamische iPhone-Anwendungen entwickeln. Anwendungsentwicklung mit HTML, CSS und JavaScript
- Visual Basic .NET. Практическое руководство для начинающего программиста
- Mastering Visual C++ 6
- Introduction to Computers and Programming using C++ and Matlab
- Professional BlazeDS: Creating Rich Internet Applications with Flex and Java (Wrox Programmer to Programmer)
Additional info for Java Object Oriented Neural Engine. The Complete Guide
Example text
Read below to see why: In a neural network that is to be trained, there needs to be at least two StreamInputSynapse objects: one to give the sample input patterns to the neural network and another to provide the net with the desired output patterns to implement some supervised learning algorithm. nextStep() method, otherwise the counters of the Monitor object will be modified twice (or more) for each cycle. To avoid this side effect, the stepCounter parameter of the StreamInputSynapse that provides the desired output data to the neural network, is set to FALSE.
In fact, to get the RMSE values, simply connect another Layer that runs on a separate Thread to the output of the TeacherSynapse object, and connect to the output of this Layer, for instance, a FileOutputSynapse object, to write the RMSE values to an ASCII file, as depicted in the following figure: Desired patterns TeachingSynapse Object InputSynapse Diff. RMSE forward() To an external OutputStream Synapse object FIFO Error TeacherSynapse RMSE LinearLayer To simplify the construction of the above described chain – teacher -> fifo -> layer – a new object (called TeachingSynapse) has been built and inserted in the core engine.
NextStep() method for each pattern read. Read below to see why: In a neural network that is to be trained, there needs to be at least two StreamInputSynapse objects: one to give the sample input patterns to the neural network and another to provide the net with the desired output patterns to implement some supervised learning algorithm. nextStep() method, otherwise the counters of the Monitor object will be modified twice (or more) for each cycle. To avoid this side effect, the stepCounter parameter of the StreamInputSynapse that provides the desired output data to the neural network, is set to FALSE.