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US 5,828,812 AGranted
Recurrent neural network-based fuzzy logic system and method
AssigneeNational Semiconductor Corporation
InventorsEmdadur Rahman Khan, William Shields Neely
Life of this patent
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Abstract
A recurrent, neural network-based fuzzy logic system includes in a rule base layer and a membership function layer neurons which each have a recurrent architecture with an output-to-input feedback path including a time delay element and a neural weight. Further included is a recurrent, neural network-based fuzzy logic rule generator wherein a neural network receives and fuzzifies input data and provides data corresponding to fuzzy logic membership functions and recurrent fuzzy logic rules.
Claims34
A recurrent neural network-based fuzzy logic apparatus comprising:
- first neural means for receiving and processing first and second pluralities of input signals and in accordance therewith providing first and second pluralities of neural signals, wherein said first plurality of input signals originates externally to said first neural means and said first plurality of neural signals corresponds to a first plurality of fuzzy logic rule antecedents;
- first time-delay means for intra-neurally receiving and time-delaying said second plurality of neural signals and in accordance therewith providing a first plurality of intra-neural recurrent signals as said second plurality of input signals;
- second neural means for receiving and processing said first plurality of neural signals from said first neural means and a plurality of antecedent signals and in accordance therewith providing a plurality of consequent signals, wherein said plurality of antecedent signals corresponds to a second plurality of fuzzy logic rule antecedents and said plurality of consequent signals corresponds to a plurality of fuzzy logic rule consequents;
- and
- second time-delay means for intra-neurally receiving and time-delaying a portion of said plurality of consequent signals and in accordance therewith providing a second plurality of intra-neural recurrent signals as said plurality of antecedent signals.
2 more elements
A neural network apparatus for generating signals corresponding to a plurality of recurrent fuzzy logic rules, comprising:
- a first plurality of neurons for receiving and selectively fuzzifying a plurality of input signals and in accordance therewith providing a plurality of fuzzified signals;
- a second plurality of neurons, coupled to said first plurality of neurons, for receiving said plurality of fuzzified signals therefrom and a first plurality of intra-neural recurrent signals and in accordance therewith providing a plurality of membership signals corresponding to a plurality of fuzzy logic membership functions;
- a first plurality of time-delay elements, coupled to said second plurality of neurons, for intra-neurally receiving and time-delaying a portion of said plurality of membership signals and in accordance therewith providing said first plurality of intra-neural recurrent signals;
- and
- a third plurality of neurons, coupled to said second plurality of neurons, for receiving said plurality of membership signals therefrom and a second plurality of intra-neural recurrent signals and in accordance therewith providing a plurality of rule signals corresponding to a plurality of recurrent fuzzy logic rules.
2 more elements
A neural network apparatus for generating a plurality of recurrent fuzzy logic rules, comprising:
- first neural means for receiving and selectively fuzzifying a plurality of input data and in accordance therewith providing a plurality of fuzzified data;
- second neural means for receiving said plurality of fuzzified data from said first neural means and a first plurality of intra-neural recurrent data and in accordance therewith providing a plurality of membership data corresponding to a plurality of fuzzy logic membership functions;
- first time-delay means for intra-neurally receiving and time-delaying a portion of said plurality of membership data and in accordance therewith providing said first plurality of intra-neural recurrent data;
- and
- third neural means for receiving said plurality of membership data from said second neural means and a second plurality of intra-neural recurrent data and in accordance therewith providing a plurality of rule data corresponding to a plurality of recurrent fuzzy logic rules.
2 more elements
A method of signal processing in accordance with recurrent neural network-based fuzzy logic, said method comprising the steps of:
- receiving and processing first and second pluralities of input signals with a first artificial neural apparatus and in accordance therewith providing first and second pluralities of neural signals, wherein said first plurality of input signals originates externally to said first artificial neural apparatus and said first plurality of neural signals corresponds to a first plurality of fuzzy logic rule antecedents;
- intra-neurally time-delaying said second plurality of neural signals and in accordance therewith providing a first plurality of intra-neural recurrent signals as said second plurality of input signals;
- processing said first plurality of neural signals from said first artificial neural apparatus and a plurality of antecedent signals with a second artificial neural apparatus and in accordance therewith providing a plurality of consequent signals, wherein said plurality of antecedent signals corresponds to a second plurality of fuzzy logic rule antecedents and said plurality of consequent signals corresponds to a plurality of fuzzy logic rule consequents;
- and
- intra-neurally time-delaying a portion of said plurality of consequent signals and in accordance therewith providing a second plurality of intra-neural recurrent signals as said plurality of antecedent signals.
2 more elements
A method of generating a plurality of recurrent fuzzy logic rules, comprising:
- receiving and selectively fuzzifying a plurality of input data with a first artificial neural apparatus and in accordance therewith providing a plurality of fuzzified data;
- receiving said plurality of fuzzified data from said first artificial neural apparatus and a first plurality of intra-neural recurrent data with a second artificial neural apparatus and in accordance therewith providing a plurality of membership data corresponding to a plurality of fuzzy logic membership functions;
- intra-neurally time-delaying a portion of said plurality of membership data and in accordance therewith providing said first plurality of intra-neural recurrent data;
- and
- receiving said plurality of membership data from said second artificial neural apparatus and a second plurality of intra-neural recurrent data with a third artificial neural apparatus and in accordance therewith providing a plurality of rule data corresponding to a plurality of recurrent fuzzy logic rules.
2 more elements
Dependencies are inferred from the claim text.