Buch, Englisch, 694 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1209 g
Reihe: Chapman Mathematical Notes
With a View toward Information Theory, Machine Learning, Wavelets, and Statistical Physics
Buch, Englisch, 694 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1209 g
Reihe: Chapman Mathematical Notes
ISBN: 978-3-031-51821-8
Verlag: Springer International Publishing
This text presents a collection of mathematical exercises with the aim of guiding readers to study topics in statistical physics, equilibrium thermodynamics, information theory, and their various connections. It explores essential tools from linear algebra, elementary functional analysis, and probability theory in detail and demonstrates their applications in topics such as entropy, machine learning, error-correcting codes, and quantum channels. The theory of communication and signal theory are also in the background, and many exercises have been chosen from the theory of wavelets and machine learning. Exercises are selected from a number of different domains, both theoretical and more applied. Notes and other remarks provide motivation for the exercises, and hints and full solutions are given for many. For senior undergraduate and beginning graduate students majoring in mathematics, physics, or engineering, this text will serve as a valuable guide as theymove on to more advanced work.
Zielgruppe
Upper undergraduate
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Algebra Lineare und multilineare Algebra, Matrizentheorie
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
- Mathematik | Informatik Mathematik Stochastik Stochastische Prozesse
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik Mathematik Mathematische Analysis Harmonische Analysis, Fourier-Mathematik
Weitere Infos & Material
Prologue.- Part I: Algebra.- Linear Algebra.- Positive Matrices.- Algebra and Error Correcting Codes.- Part II: Analysis.- Complements in Real and Complex Analysis.- Complements in Functional Analysis.- Part III: Probability and Applications.- Probability Theory.- Entropy: Discrete Case.- Thermodynamics.