You can freely build on How Hopfield Networks Use Resistors to Mimic Brain-Like Memory
This patent expired in 2005. Every claim — 0 independent, 0 dependent — is now unenforceable. Anyone can use, reproduce, manufacture, sell, or offer for sale this technology without a license.
Original assignee
California Institute of Technology
Patent granted
1987
Expired
2005
Forward citations
167
What this patent covers
This patent describes a hardware architecture where multiple amplifiers are connected in a dense matrix using resistors. Each resistor acts as a weight, determining how much the output of one amplifier influences the input of another. By setting these resistance values, the network can be programmed to store specific patterns or solve optimization problems. When the system is given a partial or noisy input, the interconnected resistors cause the circuit to settle into a stable state, effectively reconstructing the full stored pattern or finding a solution to a complex problem.
What is now free to use
All 0 claims of US 4660166 are in the public domain. Specifically:
The 0 dependent claims add narrowing limitations and are also free.
What is NOT covered
Patent expiry frees this specific invention. Separately-patented improvements made after expiry may still be protected.
Does not cover software-based neural network simulations running on standard CPUs.
Does not cover digital logic gates or traditional von Neumann computing architectures.
Does not cover learning algorithms that automatically adjust resistor values during operation (this patent focuses on fixed, programmed resistances).
Does not cover non-electronic implementations, such as optical or biological neural models.
Who is building on this today
Modern neuromorphic chip designers, such as those at Intel with the Loihi processor or startups like BrainChip, are building on the fundamental concept of using physical hardware properties to emulate neural connectivity. While the original patent is long expired, its core principle of 'compute-in-memory' remains a major area of research for low-power AI hardware.
Products built on expired version of this technology
Early hardware-based associative memory systems
Neuromorphic computing research platforms
Analog neural network circuit prototypes
How to cite this patent in your documentation
California Institute of Technology. US Patent 4660166. Electronic network for collective decision based on large number of connections between signals. Granted 1987, expired 2005. Now in the public domain.
Note: This is a convenience citation. Consult a patent attorney for formal freedom-to-operate analysis.
PatentBrief is an educational resource and does not provide legal advice. Patent expiration information is derived from USPTO records and may not reflect continuation patents, divisional filings, or separately-patented improvements. For commercial use or production decisions, obtain a formal freedom-to-operate (FTO) opinion from a registered patent attorney.