Natural Intelligence Neuromorphic Engineering
Academic Press Inc (Verlag)
978-0-12-812349-2 (ISBN)
This collaborative work offers researchers and graduate students the most up-to-date information on the theories and key applications in natural intelligence and deep learning towards real-time, error-free and automatic target recognition.
Dr. Szu has been a champion of components of human sciences (http://www.ica-wavelet.org) and brain-style computing for 2 decades; he received the INNS D. Gabor Award in 1997 and the Eduardo R. Caianiello Award in 1999 from the Italy Academy. Recently, he contributed to the unsupervised learning theory of the thermodynamic free energy of sensory pair for fusion. Besides 440 publications, (cf. https://www.researchgate.net/profile/Harold_Szu2) over dozen US patents, numerous books & journals, conference proceedings.Dr. Szu taught students “how to be creative in interdisciplinary sciences according to the Reinsurance Individual and Team Creativity Methodology, and guided over a dozen PhD students. (http://www.genealogy.math.ndsu.nodak.edu/id.php?id=44103). He received a Ph.D. in Theoretical Physics from G.E. Uhlenbeck of the Rockefeller Univ., New York, NY. He began at NRL, NSWC, ONR, and now a senior scientist at Army Night Vision Electronic Sensor Director, Ft. Belvoir, VA. Since CUA has campus on Ft. Belvoir, Prof. Szu left GWU and is appointed as Professor of CUA (http://biomedical.cua.edu/faculty-staff/Szu.cfm) • Fellow of AIMBE 2004 for breast cancer passive spectrogram diagnoses. • Fellow of IEEE (1997) for bi-sensor fusion; • Foreign Academician, RAS 1999, for unsupervised learning.• Fellow of OSA (1996) for adaptive wavelet• Fellow of SPIE since 1995 for neural nets.• Fellow of INNS (2010) for a founder and former president
1. Rule-Based Artificial Intelligence versus Artificial Neural Network Learning (ANN) Using Hinton and Jordan Deep Learning 2. Theorem of Natural Intelligence (NI): Necessary and Sufficient Conditions for D.O. Hebb Unsupervised Learning Rule 3. Improving Deep Learning through Associative Memory Expert Systems, Multiple layer Deep Learning, Compressive Sensing, Capture Novelty Detection 4. Traditional ANN, Neural Dynamics, and the Lyapunov Convergence Theorem 5. Stochastic Divide and Conquer by Fast-Simulated Annealing Searching of the Global Minimum 6. ANN Smart Sensors and Human Visual Systems Automation to the Industry 7. Biological Chaotic Neural Networks Modeling and VLSI Implementations 8. Fuzzy Logic with Possibility versus Probability Membership Functions 9. ANN Pattern Recognition and Aided Target Recognition 10. Ear-like Adaptive Wavelet Processing with Szu’s Super-Mother Wavelet Theorem 11. ANN Financial Analyses 12. How Smartphones with Big Databases Analysis ANN Can Help Public Health 13. ANN Smartphone with MEMS Smart Nodes can Nowcast Earthquakes
| Erscheinungsdatum | 05.08.2019 |
|---|---|
| Verlagsort | San Diego |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik |
| Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie | |
| Technik ► Medizintechnik | |
| ISBN-10 | 0-12-812349-4 / 0128123494 |
| ISBN-13 | 978-0-12-812349-2 / 9780128123492 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
