INTRODUCTION
Memory is the central of cognitive system. Memory is considered as storehouse of items. Without memory the cognitive system is struck here and now.It is the repositary of knowledge that guide intelligent action or make sense of world. Basically the memory system has 3 important tasks to perform. Encoding ,Storage & Retrieval. Informations from the world will be represented and stored.Some theories hold that memory is a network of nodes that associate connections among them. Memory is broadly classified into Sensory memory,Short term memory & long term memory.Sensory memory is the memory that retains representations of sensory input for brief periods of time. While short term …show more content…
When an event is experienced , it creates a pattern of activity over a set of processing units.This pattern of activity can be considered to be representation of that event.The formation of this pattern of activity trigger for creation of instructions.This is then stored in the connections among the units ,where it is avalible to use in the construction of subsequent patterns of activity. This work mainly deals with the connectionist model of …show more content…
The input signals model the post synaptic potentials. input signal’s strength depends on the strength of output signal from the sending unit combined multiplicatively with the in between connection units strength. This is considered as the connection weight. Connection weights can range from positive to negative i.e, excitatory PSP in the neuron to an inhibitory PSP.The weights vary in magnitude to model the synaptic plasticity in real neurons where learning due to experience can result in strengthening and weakening of synapses between neurons.
Connectionist models are commonly known as Parallel Distributed Processing (PDP) models. They are used to model aspects of human perception, cognition, and behaviour It include learning processes underlying such behaviour, and the storage and retrieval of information from memory. Parallel distributed processing is an artificial neural network approach that defines the distributed and parallel nature of neural processing. They gave a mathematical framework to deal with.Eight aspects included in this
Memory is the central of cognitive system. Memory is considered as storehouse of items. Without memory the cognitive system is struck here and now.It is the repositary of knowledge that guide intelligent action or make sense of world. Basically the memory system has 3 important tasks to perform. Encoding ,Storage & Retrieval. Informations from the world will be represented and stored.Some theories hold that memory is a network of nodes that associate connections among them. Memory is broadly classified into Sensory memory,Short term memory & long term memory.Sensory memory is the memory that retains representations of sensory input for brief periods of time. While short term …show more content…
When an event is experienced , it creates a pattern of activity over a set of processing units.This pattern of activity can be considered to be representation of that event.The formation of this pattern of activity trigger for creation of instructions.This is then stored in the connections among the units ,where it is avalible to use in the construction of subsequent patterns of activity. This work mainly deals with the connectionist model of …show more content…
The input signals model the post synaptic potentials. input signal’s strength depends on the strength of output signal from the sending unit combined multiplicatively with the in between connection units strength. This is considered as the connection weight. Connection weights can range from positive to negative i.e, excitatory PSP in the neuron to an inhibitory PSP.The weights vary in magnitude to model the synaptic plasticity in real neurons where learning due to experience can result in strengthening and weakening of synapses between neurons.
Connectionist models are commonly known as Parallel Distributed Processing (PDP) models. They are used to model aspects of human perception, cognition, and behaviour It include learning processes underlying such behaviour, and the storage and retrieval of information from memory. Parallel distributed processing is an artificial neural network approach that defines the distributed and parallel nature of neural processing. They gave a mathematical framework to deal with.Eight aspects included in this