Related Experiment Video
Updated: Jul 7, 2026

Aversive Associative Learning and Memory Formation by Pairing Two Chemicals in Caenorhabditis elegans
Published on: June 23, 2022
A novel high-order associative memory system via discrete Taylor series
Ning-Shou Xu1, Yun-Fei Bai, Li Zhang
1Dept. of Autom. Control, Beijing Univ. of Technol., China.
Abstract:
This paper proposes a novel high-order associative memory system (AMS) based on the discrete Taylor series (DTS). The mathematical foundation for the new AMS scheme is derived, three training algorithms are proposed, and the convergence of learning is proved. The DTS-AMS thus developed is capable of implementing error-free approximation to multivariable polynomial functions of arbitrary order. Compared with cerebellar model articulation controllers and radial basis function neural networks, it provides higher learning precision and less memory request. Furthermore, it offers less training computation and faster convergence rate than that attainable by multilayer perceptron. Numerical simulations show that the proposed DTS-AMS is effective in higher order function approximation and has potential in practical applications.
Related Concept Videos
Convergence of Taylor Series
Taylor Series
Applications of Taylor Series
Real-World Application of Classical Conditioning
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...
Associative Learning
Classical conditioning, also known...
Higher Mental Functions of Brain: Learning and Memory

