Traditionally, computer hardware such as printers and mice were plugged into sockets on the back panel of a PC, with each connector being fairly specialised in its applications.
This result tells us that neural networks have a kind of universality. No matter what function we want to compute, we know that there is a neural network which can do the job.
What's more, this universality theorem holds even if we restrict our networks to have just a single layer intermediate between the input and the output neurons - a so-called single hidden Data input and output essay. So even very simple network architectures can be extremely powerful. The universality theorem is well known by people who use neural networks.
But why it's true is not so widely understood. Most of the explanations available are quite technical. The result was very much in the air at the time, and several groups proved closely related results.
Cybenko's paper contains a useful discussion of much of that work. Another important early paper is Multilayer feedforward networks are universal approximatorsby Kurt Hornik, Maxwell Stinchcombe, and Halbert White This paper uses the Stone-Weierstrass theorem to arrive at similar results.
If you're a mathematician the argument is not difficult to follow, but it's not so easy for most people. That's a pity, since the underlying reasons for universality are simple and beautiful. In this chapter I give a simple and mostly visual explanation of the universality theorem.
We'll go step by step through the underlying ideas. You'll understand why it's true that neural networks can compute any function. You'll understand some of the limitations of the result. And you'll understand how the result relates to deep neural networks.
To follow the material in the chapter, you do not need to have read earlier chapters in this book. Instead, the chapter is structured to be enjoyable as a self-contained essay.
Provided you have just a little basic familiarity with neural networks, you should be able to follow the explanation. I will, however, provide occasional links to earlier material, to help fill in any gaps in your knowledge.
Universality theorems are a commonplace in computer science, so much so that we sometimes forget how astonishing they are. But it's worth reminding ourselves: Almost any process you can imagine can be thought of as function computation. Consider the problem of naming a piece of music based on a short sample of the piece.
That can be thought of as computing a function. Or consider the problem of translating a Chinese text into English. Or consider the problem of taking an mp4 movie file and generating a description of the plot of the movie, and a discussion of the quality of the acting. Universality means that, in principle, neural networks can do all these things and many more.
Of course, just because we know a neural network exists that can say translate Chinese text into English, that doesn't mean we have good techniques for constructing or even recognizing such a network.
This limitation applies also to traditional universality theorems for models such as Boolean circuits.A useful revision guide explaining all about specialist input devices and their uses, such as concept keyboards and interactive whiteboards, for GCSE ICT. In computing, a computer keyboard is a typewriter-style device which uses an arrangement of buttons or keys to act as mechanical levers or electronic timberdesignmag.coming the decline of punch cards and paper tape, interaction via teleprinter-style keyboards became the main input method for computers..
Keyboard keys (buttons) typically have characters engraved or printed on them, and each press. This is a quick reference of elements that are new or have been redefined in HTML5.
For each element there is a short description, a link to the specification, and a code example. The LMAX Architecture.
LMAX is a new retail financial trading platform. As a result it has to process many trades with low latency. The system is built on the JVM platform and centers on a Business Logic Processor that can handle 6 million orders per second on a single thread.
Data Input and Output Essay The methods of input of data may vary consistently. For instance, for printed questionnaires, the traditional method of input implies the use of computers’ keyboard by means of which the information that is supposed to be printed in a questionnaire is input.
The same method may be used for long documents. Essay on Computer Input/ Output What is the meaning behind Computer Input / Output Architecture and Organization? Input is the entering of data into a computer system, whereas output is the transferring of data to an external item, such as printer.