Call Us 080-41656200 (Mon-Sat: 10AM-8PM)
Free Shipping above Rs. 1499
Cash On Delivery*

Variants of Self-Organizing Maps


Marketed By :  LAP LAMBERT Academic Publishing   Sold By :  Kamal Books International  
Delivery in :  10-12 Business Days


Check Your Delivery Options

Rs. 3,651

Availability: In stock

  • Product Description

The self-organizing map (SOM) is an unsupervised learning algorithm which has been successfully applied to various applications. In the last several decades, there have been variants of SOM used in many application domains. In this work, two new SOM algorithms are developed for image quantization and compression. The first algorithm is a sample-size adaptive SOM algorithm that can be used for color quantization of images to adapt to the variations of network parameters and training sample size. Based on the sample-size adaptive self-organizing map, we use the sampling ratio of training data, rather than the conventional weight change between adjacent sweeps, as a stop criterion. As a result, it can significantly speed up the learning process. The second algorithm is a novel classified SOM method for edge preserving quantization of images using an adaptive subcodebook and weighted learning rate. The subcodebook sizes of two classes are automatically adjusted in training iterations that can be estimated incrementally. The proposed weighted learning rate updates the neuron efficiently no matter how large the weighting factor is.

Product Specifications
SKU :COC49763
AuthorChao-Huang Wang,Chung-Nan Lee and Chaur-Heh Hsieh
Number of Pages80
Publishing Year2010-09-13T00:00:00.000
Edition1 st
Book TypeProduction engineering
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-04-08 00:00:00