Learning matrix for analog signals

Claim 1

AN ARRANGEMENT FOR LEARNING AND IDENTIFYING A PLURALITY OF ELECTRIC ANALOG SIGNAL PATTERNS COMPRISING AN M X N MATRIX OF TWO OR MORE M ROWS AND ONE OR MORE N COLUMNS OF CONDUCTORS HAVING INPUT AND OUTPUT LEADS CONNECTED TO EACH ROW AND COLUMN, CONNECTING ELEMENTS ARRANGED AT THE INTERSECTING POINTS OF ROW AND COLUMN CONDUCTORS, CONTROL MEANS FOR SELECTIVELY SWITCHING ALONG AND CONTROL SIGNALS TO ROW AND COLUMN CONDUCTORS AND MAXIMUM DETECTION CIRCUIT MEANS WHEREBY DURING A LEARNING PHASE EACH OF A PLURALITY OF ANALOG SIGNAL PATTERNS APPLIED TO THE ONE OR MORE COLUMNS CAUSES THE PHYSICAL CONDITION OF ONE ROWS CONNECTING ELEMENTS TO BE CHANGED BY THE ACTION OF A COLUMN AND ROW CONTROL IN THE COURSE OF ONE OR MORE STEPS SO THAT THE CONNECTING EFFECT OF THE CONNECTING ELEMENTS BECOMES PROPORTIONAL TO THE FEATURES OF THE RESPECTIVE PATTERNS SO THAT EACH ROW REPRESENTS THE CLASS OF ONE PATTERN OUT OF A NUMBER OF M PATTERNS AND THAT DURING THE CONFIRMING OF LEARNED PHASE, WITH THE AID OF THE MAXIMUM DETECTION CIRCUIT, THE APPLICATION OF AN UNKNOWN PATTERN TO COLUMN LEADS WILL GENERATE AN OUTPUT SIGNAL INDICATIVE OF THE ROW (I) HAVING THE ROW PATTERN MOST NEARLY LIKE THE APPLIED UNKNOWN PATTERN.