Probability for Deep Learning Quantum

A Many-Sorted Algebra View
Artikelnummer: 978-0-443-24834-4
Einband: Kartonierter Einband (Kt)
Verfügbarkeit: Lieferbar in ca. 10-20 Arbeitstagen
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1. Introduction to a many sorted algebra view
2. Information geometry
3. Symplectic tomographic probability
4. Born’s rule for quantum probability calculations
5. Msa view for a random variable algebra
6. Algebra illustrations using probability indicators
7. Algebras for complex and quaternion RV
8. Msa for stochastic processes and large deviation theory
9. Probability in canonicle commutational relations
10. Applied probability in quantum
11. Entanglement
12. Quasi probability
13. Noisy Intermediate Scale Quantum NISQ Computing
14. Machine Learning Meets Quantum

1. Introduction to a many sorted algebra view
2. Information geometry
3. Symplectic tomographic probability
4. Born’s rule for quantum probability calculations
5. Msa view for a random variable algebra
6. Algebra illustrations using probability indicators
7. Algebras for complex and quaternion RV
8. Msa for stochastic processes and large deviation theory
9. Probability in canonicle commutational relations
10. Applied probability in quantum
11. Entanglement
12. Quasi probability
13. Noisy Intermediate Scale Quantum NISQ Computing
14. Machine Learning Meets Quantum

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VerlagElsevier
EinbandKartonierter Einband (Kt)
Erscheinungsjahr2025
Seitenangabe362 S.
AusgabekennzeichenEnglisch
MasseH23.5 cm x B19.1 cm 750 g
CoverlagMorgan Kaufmann Publishers In (Imprint/Brand)
AutorGiardina, Charles R.

Über den Autor 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.

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