1st Edition
Applications of Quantum Field Theory to Problems in Machine Learning Advanced Techniques Based on Path Integrals
1. QNN Using Renormalization of Fields and Supersymmetric Field Theory
2. Quantum Neural Networks: Scattering, Superconductivity, MRI, and EEG Modeling
3. QNNs with Noisy Harmonic Oscillators, Strings, and Gravitational Control
4. Adaptive Beamforming and QNNs for Evolving Brain and Field Models
5. Quantum Noisy Fields and Supersymmetric Effects: QNNs with Mixed-State Dynamics in Superstring Theory
6. Quantum Fields, Signal Theory, and QNNs via Symmetry-Broken Dynamics
7. Quantum Field Theory with Noise, Filters, Scattering, and Curved Spacetime
8. Quantum Field Theory with Noise, Filters, Scattering, and Curved Spacetime
9. QNNs and EKF for Transmission Line Control and Field Estimation
Biography
Harish Parthasarathy is Professor in the Department of Electronics & Communication Engineering at Netaji Subhas University of Technology (NSUT), New Delhi, India. Based at the university's Delhi campus, he specializes in advanced theoretical and applied research within the fields of electronics and communication systems. Professor Parthasarathy's work encompasses various aspects of electronics and communication engineering, contributing to both undergraduate and graduate-level instruction while maintaining active research engagement in his specialized areas of study.
