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memristor-circuit

Design memristor crossbar arrays for neuromorphic computing! Learn how memory resistors enable brain-like computers that merge memory and processing, just like biological neurons. Build circuits in 3 minutes.

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📚 Glossary

Memristor
Memory resistor - a two-terminal electronic device whose resistance depends on the history of current flow through it. The fourth fundamental passive circuit element.
Crossbar Array
A dense grid of memristors formed at intersections of horizontal and vertical nanowires, enabling massively parallel computation and storage.
Ron (Low Resistance State)
The resistance of a memristor when it is in its ON (conducting) state, typically representing a stored '1' or strong synaptic weight.
Roff (High Resistance State)
The resistance of a memristor when it is in its OFF (insulating) state, typically representing a stored '0' or weak synaptic weight.
Neuromorphic Computing
Computing systems inspired by the architecture and function of biological neural networks, using analog, event-driven processing rather than digital clock-based computation.
Von Neumann Bottleneck
The performance limitation in conventional computers caused by data transfer between separate memory and processing units, which memristors help eliminate.
In-Memory Computing
Performing computation directly where data is stored, avoiding the energy and time costs of data movement between memory and processor.
Resistive Switching
The physical process where applied voltage drives ion migration in a thin film, changing its resistance between high and low states.
Oxygen Vacancy
A missing oxygen atom in a metal oxide lattice that acts as a mobile charged defect, forming the conductive filaments in many memristor devices.
Conductive Filament
A nanoscale bridge of reduced metal oxide that forms across the device when oxygen vacancies accumulate, creating the low-resistance ON state.
Pinched Hysteresis
The characteristic figure-eight I-V curve of a memristor, demonstrating that resistance depends on the history of applied voltage.
Synaptic Weight
The strength of connection between two neurons, which in neuromorphic hardware is represented by the conductance (1/resistance) of a memristor.
STDP (Spike-Timing-Dependent Plasticity)
A biological learning rule where synapse strength changes based on the relative timing of pre- and post-synaptic spikes, naturally implemented by some memristors.
VMM (Vector-Matrix Multiplication)
The core mathematical operation of neural networks, performed in a single step by a memristor crossbar array using Ohm's law.
Sneak Current
Unwanted current that flows through unselected memristors in a crossbar array, causing read/write errors in large arrays.
TiO2 Memristor
The first experimentally demonstrated memristor, built by HP Labs in 2008 using a thin film of titanium dioxide.

🏆 Key Figures

Leon Chua (1971)

UC Berkeley professor who theoretically predicted the existence of the memristor in 1971 as the fourth fundamental passive circuit element, linking charge and magnetic flux through symmetry arguments

R. Stanley Williams (2008)

Led the HP Labs team that built the first physical memristor in 2008 using a titanium dioxide thin film, confirming Chua's 37-year-old prediction and launching a new field of electronics

Dmitri Strukov (2008-present)

HP Labs researcher and UC Santa Barbara professor who co-developed the physical model for the TiO2 memristor and pioneered memristive crossbar architectures for neuromorphic computing

H.-S. Philip Wong (2010s-present)

Stanford professor who advanced understanding of resistive switching mechanisms and developed practical memristor-based neural network accelerators with high computational density

Wei Lu (2010-present)

University of Michigan professor who demonstrated that memristors can naturally implement synaptic plasticity rules (STDP) and built some of the first memristor-based associative memory systems

Giacomo Indiveri (2011-present)

ETH Zurich professor who pioneered mixed-signal neuromorphic circuits and developed memristor-integrated neuromorphic processors for real-time sensory processing

💬 Message to Learners

{'encouragement': 'You are learning about a device that was predicted by pure mathematical reasoning 37 years before it was built. The memristor shows that theoretical insight and careful engineering can change the world. The chip designers who will build the first brain-equivalent computer are learning right now.', 'reminder': 'The transistor was invented in 1947 and seemed like a curiosity. Today, there are more transistors on Earth than grains of sand. The memristor, discovered in 2008, could be at the beginning of a similar revolution - computing that works like the human brain.', 'action': 'Start designing! Build crossbar arrays, write and read memristor states, explore I-V characteristics, and perform vector-matrix multiplication. Every neuromorphic chip designer started by understanding these fundamentals.', 'dream': 'Perhaps an electronics student in Dhaka will design the memristor crossbar that makes AI accessible on a $1 chip. Perhaps a young engineer in Mogadishu will create brain-like processors that run on solar power. The neuromorphic future belongs to creative minds everywhere.', 'wiaVision': 'WIA Book believes that the knowledge to design brain-like computers belongs to everyone. From Seoul to Lagos, from Zurich to Dhaka - this is your gateway to the neuromorphic computing revolution. Free forever, in the spirit of Hongik-ingan.'}

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