找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Concepts of Soft Computing; Fuzzy and ANN with P Snehashish Chakraverty,Deepti Moyi Sahoo,Nisha Ran Textbook 2019 Springer Nature Singapore

[复制链接]
楼主: 自由才谨慎
发表于 2025-3-23 11:47:38 | 显示全部楼层
发表于 2025-3-23 16:55:51 | 显示全部楼层
: The Intermediate Value Theorem,terval eigenvalue problems. Chapter 8 dealt with solving interval system of linear equations using interval analysis and in this chapter, we have focused on solving eigenvalue problems having interval parameters.
发表于 2025-3-23 18:42:59 | 显示全部楼层
Raymond F. Dickman,Peter FletcherN) because the processing is similar to the human brain. An ANN is composed of large number of highly interconnected processing elements called the neurons which work in union to solve different problems. This chapter contains preliminaries of Artificial Neural Network, types of neural network and i
发表于 2025-3-23 23:58:30 | 显示全部楼层
Shape theory and covering spaces,euron allows binary activation (1 ON or 0 OFF), i.e., it either fires with an activation 1 or does not fire with an activation of 0. If w > 0, then the connected path is said to be excitatory else it is known as inhibitory. Excitatory connections have positive weights and inhibitory connections have
发表于 2025-3-24 06:20:47 | 显示全部楼层
,Équivalence algébrique-analytique,at if two interconnected neurons are both “on” at the same time, then the weight between them should be increased. Hebbian network is a single layer neural network which consists of one input layer with many input units and one output layer with one output unit. This architecture is usually used for
发表于 2025-3-24 09:14:33 | 显示全部楼层
Topos anneles et schemas relatifsrable. Single layer perceptron consists of one input layer with one or many input units and one output layer with one or many output units. The present chapter describes about the single layer perceptron and its learning algorithm. The chapter also includes different Matlab program for calculating o
发表于 2025-3-24 11:56:40 | 显示全部楼层
Toposes, Algebraic Geometry and Logic is a forward flow of information and no feedback between the layers. Such type of network is known as feedforward networks. This chapter discusses feedforward neural network, delta learning rule. Error back propagation algorithm for unipolar and bipolar activation function are included in this chap
发表于 2025-3-24 18:02:40 | 显示全部楼层
发表于 2025-3-24 22:51:15 | 显示全部楼层
http://image.papertrans.cn/c/image/234949.jpg
发表于 2025-3-25 00:53:32 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 吾爱论文网 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
QQ|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-8-15 09:30
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表