Add to ORKGOutline of The Chapter… Section 16.2 describes CMM and the Dynamic Variable Binding Problem. Section 16.3 deals with how CMM is used as part of an inferencing engine. Section 16.4 details the important performance characteristics of CMM
AbstractUncertain causal knowledge is stored in fuzzy cognitive maps (FCMs). FCMs are fuzzy signed d...
: Statistical Parallelism (SP), is new efficient method of parallel recalling from correlation matri...
Plithogenic Cognitive Maps (PCM) introduced by Nivetha and Smarandache are extensively applied in de...
This paper briefly introduces a novel symbolic reasoning system based upon distributed associative m...
The human brain is an extremely powerful pattern recogniser, as well as being capable of displaying ...
The human brain is an extremely powerful pattern recogniser, as well as being capable of displaying ...
This paper describes an architecture based on superimposed distributed representations and distribut...
Despite their relative simplicity, Correlation Matrix Memories (CMMs) are an active area of research...
The human brain is extremely effective at performing pattern recognition, even in the presence of no...
In this paper we introduce an improved binary correlation matrix memory (CMM) with better storage ca...
This paper proposes a method for sequential data mining using correlation matrix memory. Here, we us...
Extremely large knowledge sources and efficient knowledge access characterizing future real-life art...
This paper describes the application of the Relaxation By Elimination (RBE) method to matching the 3...
The requirements for the memory structuring of intelligent systems are discussed. Simultaneously wi...
In this chapter the knowledge-based neurocomputing will be applied to expert systems. Two main appro...
AbstractUncertain causal knowledge is stored in fuzzy cognitive maps (FCMs). FCMs are fuzzy signed d...
: Statistical Parallelism (SP), is new efficient method of parallel recalling from correlation matri...
Plithogenic Cognitive Maps (PCM) introduced by Nivetha and Smarandache are extensively applied in de...
This paper briefly introduces a novel symbolic reasoning system based upon distributed associative m...
The human brain is an extremely powerful pattern recogniser, as well as being capable of displaying ...
The human brain is an extremely powerful pattern recogniser, as well as being capable of displaying ...
This paper describes an architecture based on superimposed distributed representations and distribut...
Despite their relative simplicity, Correlation Matrix Memories (CMMs) are an active area of research...
The human brain is extremely effective at performing pattern recognition, even in the presence of no...
In this paper we introduce an improved binary correlation matrix memory (CMM) with better storage ca...
This paper proposes a method for sequential data mining using correlation matrix memory. Here, we us...
Extremely large knowledge sources and efficient knowledge access characterizing future real-life art...
This paper describes the application of the Relaxation By Elimination (RBE) method to matching the 3...
The requirements for the memory structuring of intelligent systems are discussed. Simultaneously wi...
In this chapter the knowledge-based neurocomputing will be applied to expert systems. Two main appro...
AbstractUncertain causal knowledge is stored in fuzzy cognitive maps (FCMs). FCMs are fuzzy signed d...
: Statistical Parallelism (SP), is new efficient method of parallel recalling from correlation matri...
Plithogenic Cognitive Maps (PCM) introduced by Nivetha and Smarandache are extensively applied in de...