G.B. Jackson

About

G.B. Jackson is a pioneering researcher in the field of neuromorphic and analog VLSI computing, with a particular focus on hardware neural network implementations and their real-world applications. Working primarily in the early-to-mid 1990s, Jackson made significant contributions to the development of pulse-stream neural network architectures, most notably through the EPSILON chipset — a large-scale, functional analog CMOS VLSI neural processing system capable of computing an impressive 360 million synaptic connections per second. This work, which has garnered 22 and 13 citations respectively, demonstrated the practical viability of pulse-stream signaling methods and explored innovative solutions to weight storage challenges, including the development of an amorphous silicon nonvolatile memory. Jackson's research extended beyond chip design into applied robotics, investigating how hardware neural networks could enable competence acquisition in autonomous mobile robots using the EPSILON III chip — bridging the gap between theoretical neural computing and embodied intelligent systems. With a cumulative body of work that continues to be referenced in neuromorphic engineering literature, Jackson's contributions helped lay foundational groundwork for embedded neural computation and physical AI systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Pulse stream VLSI neural networks

   22 citations · 1994
2. 2
   PULSE STREAM VLSI CIRCUITS AND SYSTEMS: THE EPSILON NEURAL NETWORK CHIPSET

   13 citations · 1993
3. 3
   Competence Acquisition in an Autonomous Mobile Robot using Hardware Neural Techniques

   5 citations · 1995

Key Collaborators

Contact & Links