Neural Programming Language

نویسنده

  • Hava T. Siegelmann
چکیده

Analog recurrent neural networks have attracted much attention lately as powerful tools of automatic learning. We formally define a high level language, called NEural Langage, which is rich enough to express any computer algorithm or rulebased system. We show how to compile a NEL program to a network which computes exactly as the original program and requires the same computation time. We suggest this language along with its compiler as the ultimate bridge from symbolic to analog computation, and propose its outcome as an initial network for learning. *

برای دانلود رایگان 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

Solving Linear Semi-Infinite Programming Problems Using Recurrent Neural Networks

‎Linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints‎. ‎In this paper‎, ‎to solve this problem‎, ‎we combine a discretization method and a neural network method‎. ‎By a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem‎. ‎Then‎, ‎we use...

متن کامل

A Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems

In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...

متن کامل

A Recurrent Neural Network Model for Solving Linear Semidefinite Programming

In this paper we solve a wide rang of Semidefinite Programming (SDP) Problem by using Recurrent Neural Networks (RNNs). SDP is an important numerical tool for analysis and synthesis in systems and control theory. First we reformulate the problem to a linear programming problem, second we reformulate it to a first order system of ordinary differential equations. Then a recurrent neural network...

متن کامل

Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming

Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...

متن کامل

Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming

Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...

متن کامل

A numerical approach for optimal control model of the convex semi-infinite programming

In this paper, convex semi-infinite programming is converted to an optimal control model of neural networks and the optimal control model is solved by iterative dynamic programming method. In final, numerical examples are provided for illustration of the purposed method.

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1994