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Author  Title  Accn#  Year  Item Type  Claims 
1 
Borda, Monica 
Randomness and Elements of Decision Theory Applied to Signals 
I11928 
2021 
eBook 

2 
Helias, Moritz 
Statistical Field Theory for Neural Networks 
I09583 
2020 
eBook 


1.


Title  Randomness and Elements of Decision Theory Applied to Signals 
Author(s)  Borda, Monica;Terebes, Romulus;Malutan, Raul;Ilea, Ioana;Cislariu, Mihaela;Miclea, Andreia;Barburiceanu, Stefania 
Publication  Cham, Springer International Publishing, 2021. 
Description  XVII, 242 p. 254 illus., 168 illus. in color : online resource 
Abstract Note  This book offers an overview on the main modern important topics in random variables, random processes, and decision theory for solving realworld problems. After an introduction to concepts of statistics and signals, the book introduces many essential applications to signal processing like denoising, texture classification, histogram equalization, deep learning, or feature extraction. The book uses MATLAB algorithms to demonstrate the implementation of the theory to real systems. This makes the contents of the book relevant to students and professionals who need a quick introduction but practical introduction how to deal with random signals and processes 
ISBN,Price  9783030903145 
Keyword(s)  1. Computer science???Mathematics
2. EBOOK
3. EBOOK  SPRINGER
4. MATHEMATICAL STATISTICS
5. OPERATIONS RESEARCH
6. Operations Research and Decision Theory
7. Probability and Statistics in Computer Science
8. SIGNAL PROCESSING
9. Signal, Speech and Image Processing
10. Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
11. Statistics??

Item Type  eBook 
MultiMedia Links
Please Click here for eBook
Circulation Data
Accession#  
Call#  Status  Issued To  Return Due On  Physical Location 
I11928 


On Shelf 




2.
 
Title  Statistical Field Theory for Neural Networks 
Author(s)  Helias, Moritz;Dahmen, David 
Publication  Cham, Springer International Publishing, 2020. 
Description  XVII, 203 p. 127 illus., 5 illus. in color : online resource 
Abstract Note  This book presents a selfcontained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks. These powerful analytical techniques, which are well established in other fields of physics, are the basis of current developments and offer solutions to pressing open problems in theoretical neuroscience and also machine learning. They enable a systematic and quantitative understanding of the dynamics in recurrent and stochastic neuronal networks. This book is intended for physicists, mathematicians, and computer scientists and it is designed for selfstudy by researchers who want to enter the field or as the main text for a one semester course at advanced undergraduate or graduate level. The theoretical concepts presented in this book are systematically developed from the very beginning, which only requires basic knowledge of analysis and linear algebra 
ISBN,Price  9783030464448 
Keyword(s)  1. EBOOK
2. EBOOK  SPRINGER
3. MACHINE LEARNING
4. Mathematical Models of Cognitive Processes and Neural Networks
5. MATHEMATICAL STATISTICS
6. Neural networks (Computer science)??
7. Neurosciences
8. Probability and Statistics in Computer Science
9. STATISTICAL PHYSICS
10. Statistical Physics and Dynamical Systems

Item Type  eBook 
MultiMedia Links
Please Click here for eBook
Circulation Data
Accession#  
Call#  Status  Issued To  Return Due On  Physical Location 
I09583 


On Shelf 



 