Explanation:

Memristors, which are considered to be a sub-category of resistive RAM, are one of several storage technologies that have been predicted to replace flash memory.
Memristors are important because they are non-volatile, meaning that they retain memory without power. Memristors are a special type of resistive device that can both perform logic and store data.
A memristor is often compared to an imaginary pipe that carries water. When the water flows in one direction, the pipe's diameter expands and allows the water to flow faster -- but when the water flows in the opposite direction, the pipe's diameter contracts and slows the water's flow down.
If the water is shut off, the pipe retains its diameter until the water is turned back on. To continue the analogy, when a memristor's power is shut off, the memristor retains its resistance value.
Scientists have developed a new type of neural network chip that can dramatically improve the efficiency of teaching machines to think like humans. The network is called- Reservoir Computing System.
Researchers from University of Michigan in the US created their system using memristors, which require less space and can be integrated more easily into existing silicon-based electronics.
Researchers used a special memristor that memorises events only in the near history. Inspired by brains, neural networks are composed of neurons, or nodes, and synapses, the connections between nodes.
Reservoir computing systems built with memristors can skip most of the expensive training process and still provide the network the capability to remember. This is because the most critical component of the system – the reservoir – does not require training.
For example, a system can process a new photo and correctly identify a human face, because it has learned the features of human faces from other photos in its training set.