Analysis of the Internal Neural Networks for Ma

نویسنده

  • Wan CHAN
چکیده

The internal representation of the training patterns of multi-layer perceptrons was examined and we demonstrated that the connection weights between layers are effectively transforming the representation format of the information from one layer to another one in a meaningful way. The internal code, which can be in analog or binary form, is found to be dependent on a number of factors, including the choice of an appropriate representation of the training patterns, the similarities between the patterns as well as the network structure; i.e. the number of hidden layers and the number of hidden units in each layer. In supervised neural networks, such as multi-layer perceptrons [Rumelhart, Hinton & Williams 19861, information is acquired by presenting some training examples to the network in the training process. These examples are pairs of input and output patterns. A set of connection weights is then found iteratively using the generalised delta rule and it is reserved for the classification process in the recalling phase. At present, there is no explicit guide-lines for both the choice of the size of the network and the representation format of the training examples. Trial and error has been used to decide the number of hidden layers and the number hidden units in each layer. Previous studies have shown that the number of hidden units in a multi-layer perceptron affects the performance of the network. For examples, the convergence speed and the recognition rate vary with the number of hidden units [Burr 19881. In this paper, the approach of regarding the hidden layers as the transformation process in the hyper-space were used. We illustrate that a back propagation network with internal layers solves some classification problem intelligently by using this transformation idea. In addition, we show that the internal representation of information can be affected by some characteristics of the training patterns and the architecture of the network.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network

Abstract   Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...

متن کامل

Robust Fault Detection on Boiler-turbine Unit Actuators Using Dynamic Neural Networks

Due to the important role of the boiler-turbine units in industries and electricity generation, it is important to diagnose different types of faults in different parts of boiler-turbine system. Different parts of a boiler-turbine system like the sensor or actuator or plant can be affected by various types of faults. In this paper, the effects of the occurrence of faults on the actuators are in...

متن کامل

Performance Analysis of a New Neural Network for Routing in Mesh Interconnection Networks

Routing is one of the basic parts of a message passing multiprocessor system. The routing procedure has a great impact on the efficiency of a system. Neural algorithms that are currently in use for computer networks require a large number of neurons. If a specific topology of a multiprocessor network is considered, the number of neurons can be reduced. In this paper a new recurrent neural ne...

متن کامل

Modeling of Texture and Color Froth Characteristics for Evaluation of Flotation Performance in Sarcheshmeh Copper Pilot Plant, Using Image Analysis and Neural Networks

Texture and color appearance of froth is a discreet qualitative tool for evaluating the performance of flotation process. The structure of a froth developed on the flotation cell has a significant effect on the grade and recovery of copper concentrate. In this work, image analysis and neural networks have been implemented to model and control the performance of such a system. The result reveals...

متن کامل

Application of Artificial Neural Networks for Analysis of Flexible Pavements under Static Loading of Standard Axle

In this study, an artificial neural network was developed in order to analyze flexible pavement structure and determine its critical responses under the influence of standard axle loading. In doing so, more than 10000 four-layered flexible pavement sections composed of asphalt concrete layer, base layer, subbase layer, and subgrade soil were analyzed under the impact of standard axle loading. P...

متن کامل

Performance Analysis of a New Neural Network for Routing in Mesh Interconnection Networks

Routing is one of the basic parts of a message passing multiprocessor system. The routing procedure has a great impact on the efficiency of a system. Neural algorithms that are currently in use for computer networks require a large number of neurons. If a specific topology of a multiprocessor network is considered, the number of neurons can be reduced. In this paper a new recurrent neural ne...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1999