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Analog Current-Mode Computational Circuits for Artificial Neural Networks

Medium: Buch
ISBN: 978-3-032-03988-0
Verlag: Springer
Erscheinungstermin: 07.11.2025
Lieferfrist: bis zu 10 Tage

This book discusses in detail low-voltage low-power designs for minimizing the hardware resources required by neural network implementations. The novel method presented in this book for an accurate realization of activation functions for artificial neural networks (ANNs), is based on specific superior-order approximation functions. The author describes analog implementations in CMOS technology to increase the speed of operation, while reducing the hardware resources required for obtaining these approximation functions. Original architectures presented in this book, used for implementing previous CMOS computational structures, allow for operation independent of technological errors and temperature variations. SPICE simulations confirm the theoretically estimated results for previously presented CMOS computational structures, developed  for ANNs and artificial intelligence applications.


Produkteigenschaften


  • Artikelnummer: 9783032039880
  • Medium: Buch
  • ISBN: 978-3-032-03988-0
  • Verlag: Springer
  • Erscheinungstermin: 07.11.2025
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2025
  • Serie: Analog Circuits and Signal Processing
  • Produktform: Gebunden, HC runder Rücken kaschiert
  • Gewicht: 874 g
  • Seiten: 397
  • Format (B x H x T): 160 x 241 x 27 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

Introduction.- Superior-order approximation functions for generating sigmoidal activation functions.- Superior-order approximation functions for generating radial basis activation functions.- Superior-order approximation functions for artificial neural networks applications.- Analysis and design of analog function synthesizers for implmenting sigmoidal activation functions.- Analysis and design of analog function synthesizers for generating radial basis activation functions.- Analysis and design of analog function synthesizers for artificial neural networks applications.- Low-voltage low-power current-mode CMOS computational circuits for implementing activation functions.- Conclusions.