03604nam 22005655 450 991103931970332120251107114906.09783032039897(electronic bk.)978303203988010.1007/978-3-032-03989-7(MiAaPQ)EBC32405110(Au-PeEL)EBL32405110(CKB)42032179700041(DE-He213)978-3-032-03989-7(EXLCZ)994203217970004120251107d2025 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAnalog Current-Mode Computational Circuits for Artificial Neural Networks /by Cosmin Radu Popa1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (233 pages)Analog Circuits and Signal Processing,2197-1854Print version: Popa, Cosmin Radu Analog Current-Mode Computational Circuits for Artificial Neural Networks Cham : Springer,c2025 9783032039880 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.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.Analog Circuits and Signal Processing,2197-1854Electronic circuit designEmbedded computer systemsCooperating objects (Computer systems)Electronics Design and VerificationEmbedded SystemsCyber-Physical SystemsElectronic circuit design.Embedded computer systems.Cooperating objects (Computer systems).Electronics Design and Verification.Embedded Systems.Cyber-Physical Systems.621.3815Popa Cosmin Radu1061259MiAaPQMiAaPQMiAaPQ9911039319703321Analog Current-Mode Computational Circuits for Artificial Neural Networks4454516UNINA