Paperback
Algebraic structures unlock the future of AI and quantum computing.

Many-Sorted Algebras for Deep Learning and Quantum Technology

$507.01

  • Paperback

    422 pages

  • Release Date

    5 February 2024

Check Delivery Options

Summary

Many-Sorted Algebras for Deep Learning and Quantum Technology

This book offers a comprehensive exploration of how many-sorted algebras can be applied to revolutionize advancements in both deep learning and quantum technology.

The text begins by laying a strong theoretical foundation in many-sorted algebra, explaining its core concepts and properties in a clear and accessible manner. It then meticulously demonstrates how these algebraic structures provide a powerful framework…

Book Details

ISBN-13:9780443136979
ISBN-10:0443136971
Author:Charles R. Giardina
Publisher:Elsevier Science & Technology
Imprint:Morgan Kaufmann Publishers In
Format:Paperback
Number of Pages:422
Release Date:5 February 2024
Weight:860g
Dimensions:191mm x 235mm
A-Format
B-Format
C-Format
Many-Sorted Algebras for Deep Learning and Quantum Technology by Charles R. Giardina - ISBN: 9780443136979
191 × 235 mm
A4
mm / in
About The Author

Charles R. Giardina

Charles R. Giardina was born in the Bronx, NY, on December 29, 1942. He received the B.S. degree in mathematics from Fairleigh Dickinson University, Rutherford, NJ, and the M.S. degree in mathematics from Carnegie Institute of Technology, Pittsburgh, PA. He also received the M.E.E. degree in 1969, and the Ph.D. degree in mathematics and electrical engineering in 1970 from Stevens Institute of Technology, Hoboken, NJ. Dr. Giardina was Professor of Mathematics, Electrical Engineering, and Computer Science at Fairleigh Dickinson University from 1965 to 1982. From 1982 to 1986, he was a Professor at the Stevens Institute of Technology. From 1986 to 1996, he was a Professor at the College of Staten Island, City University of New York. From 1996, he was with Bell Telephone Laboratories, Whippany, NJ, USA. His research interests include digital signal and image processing, pattern recognition, artificial intelligence, and the constructive theory of functions. Dr. Giardina has authored numerous papers in these areas, and several books including, Mathematical Models for Artificial Intelligence and Autonomous Systems, Prentice Hall; Matrix Structure Image Processing, Prentice Hall; Parallel Digital Signal Processing: A Unified Signal Algebra Approach, Regency; Morphological Methods in Image and Signal Processing, Prentice Hall; Image Processing – Continuous to Discrete: Geometric, Transform, and Statistical Methods, Prentice Hall; and A Unified Signal Algebra Approach to Two-Dimensional Parallel Digital Signal Processing, Chapman and Hall/CRC Press.

Returns

This item is eligible for free returns within 30 days of delivery. See our returns policy for further details.