tailieunhanh - neural networks algorithms applications and programming techniques phần 2

vì vậy chúng tôi không biết chính xác những gì những hạn chế. Công nghệ, mặc dù hơn 30 tuổi tại văn bản này, vẫn còn đang nổi lên và xứng đáng được giám sát chặt chẽ. Chúng tôi phải luôn luôn được nhận thức của cả những điểm mạnh và những hạn chế của công cụ của chúng tôi. | 30 Introduction to ANS Technology levels. To address the issue of scaling we may need to learn how to combine small networks and to place them under the control of other networks. Of course a small network in the brain challenges our current simulation capabilities so we do not know exactly what the limitations are. The technology although over 30 years old at this writing is still emerging and deserves close scrutiny. We should always be aware of both the strengths and the limitations of our tools. ANS SIMULATION We will now consider several techniques for simulating ANS processing models using conventional programming methodologies. After presenting the design guidelines and goals that you should consider when implementing your own neural-network simulators we will discuss the data structures that will be used throughout the remainder of this text as the basis for the network-simulation algorithms presented as a part of each chapter. The Need for ANS Simulation Most of the ANS models that we will examine in subsequent chapters share the basic concepts of distributed and highly interconnected PEs. Each network model will build on these simple concepts implementing a unique learning law an interconnection scheme . fully interconnected sparsely interconnected unidirectional and bidirectional and a structure to provide systems that are tailored to specific kinds of problems. If we are to explore the possibilities of ANS technology and to determine what its practical benefits and limitations are we must develop a means of testing as many as possible of these different network models. Only then will we be able to determine accurately whether or not an ANS can be used to solve a particular problem. Unfortunately we do not have access to a computer system designed specifically to perform massively parallel processing such as is found in all the ANS models we will study. However we do have access to a tool that can be programmed rapidly to perform any type of