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[null,"1.","Record Nr.",null,"UNINA9910497099703321"]
[null,null,"Autore",null,"Erokhin Victor"]
[null,null,"Titolo",null,"Fundamentals of Organic Neuromorphic Systems"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing AG, , 2021"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-030-79492-X"]
[null,null,"Descrizione fisica",null,"1 online resource (270 pages)"]
[null,null,"Soggetti",null,"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Acknowledgments -- Introduction -- Involvement of Same Elements for Memorizing and Processing of Information -- Variation of Electrical Properties According to the Hebbian (or Alternative) Rule (Electronic Synapse) -- Possibility of Working in Auto-Oscillation Mode -- Formation of Stable Chains of the Signal Transfer -- Materials Used for Electronic Compounds Must Allow Self-Organisation into 3D Systems Mimicking Intrinsic Brain Functions -- Contents -- About the Author -- Chapter 1: Memristive Devices and Circuits -- 1.1 Determination of Memristor -- 1.2 Mnemotrix -- 1.3 First Mention About the Experimental Realization of Memristor -- 1.4 Inorganic Memristive Devices -- 1.5 Memristive Devices with the Organic Materials -- Chapter 2: Organic Memristive Device -- 2.1 Basic Materials -- 2.2 Structure and Working Principle of the Device -- 2.3 Electrical Characteristics of the Device -- 2.4 Device Working Mechanism -- 2.4.1 Spectroscopy -- 2.4.2 X-Ray Fluorescence -- 2.5 Electrical Characteristics in a Pulse Mode -- 2.6 Optimization of Properties and Stability of the Device -- 2.6.1 Stability of Organic Memristive Device Properties -- 2.6.2 Optimization of the Device Architecture -- 2.6.3 Role of the Electrolyte -- 2.7 Organic Memristive Devices with Channels, Formed by Layer-by-Layer Technique -- Chapter 3: Oscillators Based on Organic Memristive Devices -- Chapter 4: Models -- 4.1 Phenomenological Model -- 4.2 Simplified Model of the Organic Memristive Device Function -- 4.3 Electrochemical Model -- 4.4 Optical Monitoring of the Resistive States -- Chapter 5: Logic Elements and Neuron Networks -- 5.1 Logic Elements with Memory -- 5.1.1 Element ``OR´´ with Memory -- 5.1.2 Element ``AND´´ with "]
[{"$nulls":4},"Memory -- 5.1.3 Element ``NOT´´ with Memory."]
[{"$nulls":4},"5.1.4 Comparison of Logic Elements with Memory, Based on Organic and Inorganic Memristive Devices -- 5.2 Perceptrons -- 5.2.1 Single Layer Perceptron -- 5.2.2 Double Layer Perceptron -- Chapter 6: Neuromorphic Systems -- 6.1 Learning of Circuits Based on a Single Memristive Device -- 6.1.1 DC Mode -- 6.1.2 Pulse Mode -- 6.2 Training of Networks with Several Memristive Elements -- 6.3 Training Algorithms -- 6.4 Electronic Analog of the Part of the Nervous System of Pond Snail (Lymnaea Stagnalis) -- 6.4.1 Biological Benchmark -- 6.4.2 Experimentally Realized Circuit, Mimicking the Architecture and Properties of the Pond Snail Nervous System Part -- 6.5 Cross Talk of Memristive Devices During Signal Pathways Formation Process -- 6.6 Effect of Noise -- 6.7 Frequency Driven Short-Term Memory and Long-Term Potentiation -- 6.8 Spike-Timing-Dependent Plasticity (STDP) Learning in Memristive Systems -- 6.8.1 STDP in Circuits with Polyaniline-Based Memristive Devices -- 6.8.2 STDP in Circuits with Parylene-Based Memristive Devices -- 6.8.3 Classic Conditioning of Polyaniline-Based Memristive Devices Systems -- 6.8.4 Classic Conditioning of Parylene-Based Memristive Devices Systems -- 6.9 Coupling with Living Beings -- Chapter 7: 3D Systems with Stochastic Architecture -- 7.1 Free-Standing Fibrillar Systems -- 7.2 Stochastic Networks on Frames with Developed Structure -- 7.3 3D Stochastic Networks, Based on Phase Separation of Materials -- 7.3.1 Stabilized Gold Nanoparticles -- 7.3.2 Block Copolymer -- 7.3.3 Fabrication of 3D Stochastic Network -- 7.3.4 Training of Stochastic 3D Network, Based on Phase Separation of Materials -- 7.3.5 Evidence of 3D Nature of the Realized Stochastic System -- 7.4 Modeling of Adaptive Electrical Characteristics of Stochastic 3D Network -- 7.4.1 Single Memristive Device -- 7.4.2 Structure of the Network -- 7.4.3 Network Dynamics."]
[{"$nulls":4},"7.4.4 Modeling of Experimental Results, Obtained on 3D Stochastic Networks -- Conclusions -- References -- Index."]