Abstract: A neural network element, outputting an output signal in response to a plurality of input signals, comprises a history memory for accumulating and storing the plurality of input signals in a temporal order as history values. It also includes an output module for outputting the output signal when an internal state exceeds a predetermined threshold value, the internal state being based on a sum of the product of a plurality of input signals and corresponding coupling coefficients. The history values depend on change of the internal state. The neural network element is configured to subtract a predetermined value from the internal state immediately after the output module fires and performs learning for reinforcing or attenuating the coupling coefficient according to the history values after the output module fires.

Abstract: A neural network element, outputting an output signal in response to a plurality of input signals, comprises a history memory for accumulating and storing the plurality of input signals in a temporal order as history values. It also includes an output module for outputting the output signal when an internal state exceeds a predetermined threshold value, the internal state being based on a sum of the product of a plurality of input signals and corresponding coupling coefficients. The history values depend on change of the internal state. The neural network element is configured to subtract a predetermined value from the internal state immediately after the output module fires and performs learning for reinforcing or attenuating the coupling coefficient according to the history values after the output module fires.

Abstract: A temporal learning neural network includes a plurality of temporal learning neural processing elements and an input/output control section. Each element includes a calculation device and a learning device. The calculation device includes an input memory section and a response calculation circuit. The learning device includes a learning processing circuit and a history evaluation circuit. The calculation circuit calculates a sum of a total summation value of a product of input values and connection efficacies, and an internal potential, compares the sum with a predetermined threshold value, outputs a 1 or 0 signal depending on the comparison and substitutes internal potential of a next time for the sum. The processing circuit receives an input history evaluation value when the calculation circuit has produced an output 1 signal which strengthens, weakens or leaves unchanged the connection efficacies depending on the comparison.

Abstract: The invention relates to a method and apparatus for freezing a sample by solidifying a liquid contained in the sample and widen the distance within the sample where the same is amorphously solidified. For this purpose, the sample is cooled immediately after being irradiated with an electromagnetic wave. The apparatus includes an electromagnetic irradiating means for irradiatine an electromagnetic wave on a sample immediately before freezing thereof.