By Alan M. F. Souza, Fabio M. Soares
Substantial amounts of knowledge are produced each moment. during this context, neural networks develop into a strong strategy to extract invaluable wisdom from quite a lot of uncooked, doubtless unrelated info. essentially the most hottest languages for neural community programming is Java because it is less complicated to jot down code utilizing it, and lots of the most well-liked neural community applications round exist already for Java. This makes it a flexible programming language for neural networks.
This publication can provide a whole walkthrough of the method of constructing simple to complex sensible examples according to neural networks with Java.
You will first research the fundamentals of neural networks and their means of studying. We then concentrate on what Perceptrons are and their beneficial properties. subsequent, you are going to enforce self-organizing maps utilizing the suggestions you've discovered. additionally, you'll find out about a number of the purposes which are offered during this ebook corresponding to climate forecasting, sickness prognosis, purchaser profiling, and characters popularity (OCR). eventually, you are going to study the way to optimize and adapt neural networks in genuine time.
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Additional info for Neural Network Programming with Java
Sample text
Nowadays, Java is present in many devices that are part of our daily life. In an object-oriented language, such as Java, we deal with classes and objects. A class is a blueprint of something in the real world, and an object is an instance of this blueprint, something like a car (class referring to all and any car) and my car (object referring to a specific car—mine). Java classes are usually composed of attributes and methods (or functions), that include objects-oriented programming (OOP) concepts.
Let's suppose that we present for the network a set of N records containing pairs of X and T variables, whereas X are the input-independent values and T are the target values dependent on X. Let's consider the neural network as a mathematical function ANN() that produces Y on the output when being fed with the X values. info How Neural Networks Learn For each x value given to the ANN, it will produce a y value that when compared to the t value gives an error e. However, this is a mere individual error measurement per data point.
Java One advantage of OOP languages is the ease to document the program in Unified Modeling Language (UML). UML class diagrams present classes, attributes, methods, and relationships between classes in a very simple and straightforward manner, thus helping the programmer and/or stakeholders to understand the project as a whole. info Chapter 1 Now, let's apply these classes and get some results. The code shown next has a test class, a main method with an object of the NeuralNet class called n. When this method is called (by executing the class), it calls the initNet() and printNet() methods from the object n, generating the following result shown in the figure right after the code.