Page 330 - Artificial Intelligence in the Age of Neural Networks and Brain Computing

Index 323

Schizophrenia, 87, 88f supervised learning for classification of learned
Schmidhuber’s study, 287e288 patterns, 128
SDL. See Supervised deep learning (SDL) Spontaneous break of symmetry (SBS), 95
Second computational paradigm, 40e41 SQUIDs. See Superconducting quantum
Second Gen AI, 56e57 interference devices (SQUIDs)
Second-order cybernetics, 84e85 SRM. See Spike Response Models (SRM)
Secure operations, 246e247 SSL. See Semisupervised learning (SSL)
Self-adaptive fuzzy inference network SSVEP. See Steady-state visual evoked potential
(SaFIN), 120 (SSVEP)
Self-adaptive kernel machined (SAKM), 120 Stacked autoencoders (SAEs), 223e224,
Self-normalizing, 41 232e235
Self-organizing fuzzy modified least-squares Stationarity/time invariance, 246e247
network (SOFMLS network), 120 STDP. See Spike-time dependent plasticity
Self-Organizing maps (SOM), 114 (STDP)
Semisupervised learning (SSL), 129, 130f, Steady-state visual evoked potential (SSVEP), 236
221e222 STM. See Short-term memory (STM)
Sensitivity, 150 Stream-shroud resonances, 46e47
Separate Testing Set, 149 Stress relief, 106
Serial DL schemes, 232e233, 233f Stroop task, 196
Short-term memory (STM), 45, 192, 284 Superconducting quantum interference devices
Sigmoidal function, 10 (SQUIDs), 232
Sigmoidal neuron, bootstrap learning with, Supervised deep learning (SDL), 67
10e12, 11f Supervised learning (SL), 221e222
Silicon-based digital computing machines, 55 for classification of learned patterns, 128
Similarity network fusion (SNF), 270, 271f Supervised LMS algorithm, 16
Single-level neuroevolution, 295e296 Support Vector Machines (SVM), 235
Size-weight-speed-power (SWSP), 54e55 Surface-shroud resonances, 46e47
SL. See Supervised learning (SL) “Survivor natural wisdom”, 56
Slow-wave sleep, 287 SVM. See Support Vector Machines (SVM)
Slowing effect, 228 SWSP. See Size-weight-speed-power (SWSP)
Smart solutions, 246 Symbolic AI approaches, 208
SNF. See Similarity network fusion (SNF) Synapse, 22e25, 23f
SNN. See Spiking neural network (SNN) to ephapsis
SNN reservoir module (SNNr module), 125 embodied cognition, 97e105
Social cognitive abilities, 39e40 ephapsis, 95e97
SOFMLS network. See Self-organizing fuzzy neural networks and neural fields, 93e95
modified least-squares network (SOFMLS wearable personal assistants, 105e108
network) neuron, dendrites, and a synapse, 24f
SOM. See Self-Organizing maps (SOM) Synaptic cleft, 22e23
Specificity, 150 Synaptic plasticity, 25, 285e286
Spectral-pitch-and-timbre resonances, 46e47 Synaptic scaling, 24e25
Spike Response Models (SRM), 121 Synchronization, 211e213
Spike-time dependent plasticity (STDP), 122
Spike-timing-dependent plasticity, 285e286 T
Spiking neural network (SNN), 121. See also t-Stochastic Neighbor Embedding (t-SNE),
Artificial neural network (ANN); 260e261
Convolutional neural networks (CNN); Telephone channels, 8
Deep neural networks (DNNs) Temporal difference model (TD model),
as brain-inspired ANN 194, 197
applications and implementations for AI, 124 Tensor Flow Python Language, 59
principles, methods, and examples, Tensor Processing Units (TPU), 206e207
121e124, 121f TES. See Inverse Total Enrichment Score (TES)