The Cavity Method: a New Approach to Neural Network Analysis
نویسنده
چکیده
Using the cavity method I derive the microscopic equations and their stability condition for learning in neural networks. Iterating the microscopic equations provides a general algorithm for learning. Macroscopic results agree with the replica theory and the Almeida-Thouless stability condition. They are applied to derive the evolution equations of the overlap order parameter and the noise parameter in the retrieval dynamics of feedforward neural networks.
منابع مشابه
A Neural Network Model to Solve DEA Problems
The paper deals with Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN). We believe that solving for the DEA efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. In this paper, a new neural network model is used to estimate the inefficiency of DMUs in large datasets.
متن کاملA hybrid approach to supplier performance evaluation using artificial neural network: a case study in automobile industry
For many years, purchasing and supplier performance evaluation have been discussed in both academic and industrial circles to improve buyer-supplier relationship. In this study, a novel model is presented to evaluate supplier performance according to different purchasing classes. In the proposed method, clustering analysis is applied to develop purchasing portfolio model using available data in...
متن کاملForward kinematic analysis of planar parallel robots using a neural network-based approach optimized by machine learning
The forward kinematic problem of parallel robots is always considered as a challenge in the field of parallel robots due to the obtained nonlinear system of equations. In this paper, the forward kinematic problem of planar parallel robots in their workspace is investigated using a neural network based approach. In order to increase the accuracy of this method, the workspace of the parallel robo...
متن کاملCombined Unfolded Principal Component Analysis and Artificial Neural Network for Determination of Ibuprofen in Human Serum by Three-Dimensional Excitation–Emission Matrix Fluorescence Spectroscopy
This study describes a simple and rapid approach of monitoring ibuprofen (IBP). Unfolded principal component analysis-artificial neural network (UPCA-ANN) and excitation-emission spectra resulted from spectrofluorimetry method were combined to develop new model in the determination of IBF in human serum samples. Fluorescence landscapes with excitation wavelengths from 235 to 265 nm and emission...
متن کاملCombined Unfolded Principal Component Analysis and Artificial Neural Network for Determination of Ibuprofen in Human Serum by Three-Dimensional Excitation–Emission Matrix Fluorescence Spectroscopy
This study describes a simple and rapid approach of monitoring ibuprofen (IBP). Unfolded principal component analysis-artificial neural network (UPCA-ANN) and excitation-emission spectra resulted from spectrofluorimetry method were combined to develop new model in the determination of IBF in human serum samples. Fluorescence landscapes with excitation wavelengths from 235 to 265 nm and emission...
متن کاملP/E Modeling and Prediction of Firms Listed on the Tehran Stock Exchange; a New Approach to Harmony Search Algorithm and Neural Network Hybridization
Investors and other contributors to stock exchange need a variety of tools, measures, and information in order to make decisions. One of the most common tools and criteria of decision makers is price-to earnings per share ratio. As a result, investors are in pursuit of ways to have a better assessment and forecast of price and dividends and get the highest returns on their investment. Previous ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007