ADAPTIVE STOCHASTIC CONTENT-ADDRESSABLE MEMORY

IT IS PROPOSED TO EXPLORE THE FEASIBILITY OF ADDING ADAPTIVE AND STOCHASTIC FEATURES TO A CONTENT-ADDRESSABLE MEMORY (CAM) IN SUCH A MANNER THAT THE DEVICE BECOMES CAPABLE OF LEARNING FROM INSTRUCTION AND EXPERIENCE. THE ALGORITHM OF THE ADAPTIVE STOCHASTIC CONTENTADDRESSABLE MEMORY (ASCAM) IS THE SAME AS THAT OF ADAPTIVE NEURAL NETWORKS, VIZ., ITERATIVE THRESHOLDED MATRIX-BINARY VECTOR MULTIPLICATION, WITH ADAPTION IN THE FORM OF FACILITATION. THE LATTER COMES IN TWO KINDS: S-FACILITATION, WHICH INVOLVES THE INCREASE OF THE MAGNITUDE OF THOSE MATRIX ELEMENTS WHICH HAVE REPEATEDLY CONTRIBUTED TO OUTPUT IN THE MATRIX-VECTOR MULTIPLICATION IN THE RECENT PAST. TFACILITATION INVOLVES THE DECREASE OF THRESHOLD OF THOSE COMPONENTS WHICH HAVE REPEATEDLY HAD AN OUTPUT IN THE RECENT PAST. THE CAM STORES A SET OF BINARY WORDS; UPON INPUT OF A WORD WHICH HAS A SMALL HAMMING DISTANCE TO ONE OF THE STORED WORDS, THE CAM OUTPUTS THIS STORED WORD WITHIN A FEW MACHINE CYCLES. AN OPTICAL IMPLEMENTATION OF THE ASCAM IS ENVISIONED. THE FEASIBILITY EXPLORATION WILL BE CONDUCTED THROUGH COMPUTER CALCULATIONS ON A 64-BIT ASCAM. FOR DIFFERENT FACILITATION AND STOCHASTIC SCHEMES, THE LEARNING ABILITY OF THE ASCAM WILL BE INVESTIGATED.