The layer effect on multi-layer cellular neural networks

نویسندگان
چکیده

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Stability of Multi-Layer Cellular Neural/Nonlinear Networks

We have found a formalism that lets us present generalizations of several stability theorems (see Chua & Roska, 1990; Chua & Wu, 1992; Gilli, 1993; Forti, 2002] on Multi-Layer Cellular Neural/Nonlinear Networks (MLCNN) formerly claimed for Single-Layer Cellular Neural/Nonlinear Networks (CNN). The theorems were selected with special regard to usefulness in engineering applications. Hence, in co...

متن کامل

The Application of Multi-Layer Artificial Neural Networks in Speckle Reduction (Methodology)

Optical Coherence Tomography (OCT) uses the spatial and temporal coherence properties of optical waves backscattered from a tissue sample to form an image. An inherent characteristic of coherent imaging is the presence of speckle noise. In this study we use a new ensemble framework which is a combination of several Multi-Layer Perceptron (MLP) neural networks to denoise OCT images. The noise is...

متن کامل

Power Control in Multi-Layer Cellular Networks

We investigate the possible performance gains of power control in multi-layer cellular systems where microcells and picocells are distributed within macrocells. Although multilayers in cellular networks help increase system capacity and coverage, and can reduce total energy consumption; they cause interference, reducing the performance of the network. Therefore, downlink transmit power levels o...

متن کامل

The Effects of Quantization on Multi-Layer Feedforward Neural Networks

In this paper we investigate the combined effect of quantization and clipping on multilayer feedforward neural networks (MLFNN). Statistical models are used to analyze the effects of quantization in a digital implementation. We analyze the performance degradation caused as a function of the number of fixed-point and floating-point quantization bits in the MLFNN. To analyze a true nonlinear neur...

متن کامل

SEISMIC DESIGN OF DOUBLE LAYER GRIDS BY NEURAL NETWORKS

The main contribution of the present paper is to train efficient neural networks for seismic design of double layer grids subject to multiple-earthquake loading. As the seismic analysis and design of such large scale structures require high computational efforts, employing neural network techniques substantially decreases the computational burden. Square-on-square double layer grids with the va...

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

ژورنال

عنوان ژورنال: Applied Mathematics Letters

سال: 2013

ISSN: 0893-9659

DOI: 10.1016/j.aml.2013.01.013