Tell me some models designed for the purpose of emulating the functions of associative memory in human brain

Hopfield Network Model: This is one of the most widely used models for associative memory. It is a type of recurrent artificial neural network that is capable of storing and retrieving patterns.

Boltzmann Machine Model: This model is also a type of recurrent artificial neural network that is capable of learning and storing patterns. It is based on the principles of statistical mechanics and uses a stochastic approach to learning.

Self-organizing Map Model: This model is based on the concept of competitive learning and is used for clustering and visualization of high-dimensional data. It is also known as a Kohonen network.

Neural Gas Model: This is another type of unsupervised neural network that is used for clustering and pattern recognition. It is based on the concept of self-organizing maps and uses a competitive learning approach.

ART Model: Adaptive Resonance Theory (ART) is a family of neural networks that are used for pattern recognition and classification. They are based on the principles of self-organization and self-stabilization.