Neural Networks in Atmospheric Remote Sensing

Neural Networks in Atmospheric Remote Sensing

English | April 30, 2009 | ISBN: 1596933720 | 234 Pages | PDF | 15 MB

A neural network refers to interconnecting artificial neurons that mimic the properties of biological neurons to perform sophisticated, intelligent tasks. This authoritative reference offers a comprehensive understanding of the underpinnings and practical applications of artificial neural networks and their use in the retrieval of geophysical parameters. Professionals find expert guidance on the development and evaluation of neural network algorithms that process data from a new generation of hyperspectral sensors. Engineers discover how to use neural networks to approximate remote sensing inverse functions with emphasis on model selection, preprocessing, initialization, training, and performance evaluation.

Download:

http://longfiles.com/kvxyk0ffjf4l/Neural_Networks_in_Atmospheric_Remote_Sensing.pdf.html

[Fast Download] Neural Networks in Atmospheric Remote Sensing


Related eBooks:
Practical Power Plant Engineering: A Guide for Early Career Engineers
Consensus Problem of Delayed Linear Multi-agent Systems: Analysis and Design
Pulse-width Modulated DC-DC Power Converters
Advanced Technologies in Robotics and Intelligent Systems: Proceedings of ITR 2019
Index Generation Functions
Trustworthy Hardware Design: Combinational Logic Locking Techniques
3D Stacked Chips: From Emerging Processes to Heterogeneous Systems
Multilayered Low Temperature Cofired Ceramics
Basic Circuit Analysis For Electronics Through Experimentation
Mike Meyers' CompTIA Security+ Certification Guide (Exam SY0-501), 2nd Edition
Low-Power Analog Techniques, Sensors for Mobile Devices, and Energy Efficient Amplifiers
Mobile Robotics: Solutions and Challenges
Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.