Abstract: A memory system configured to provide thermal regulation of a plurality of memory devices is disclosed. The memory system comprises a memory device coupled to a bus. Additionally, the memory system also comprises a controller coupled to the bus. The controller determines an operating temperature of the memory device. Based on the operating temperature of the memory device, the controller is further operable to manipulate the operation of the memory system.

Abstract: The neural engine (20) is a hardware implementation of a neural network for use in real-time systems. The neural engine (20) includes a control circuit (26) and one or more multiply/accumulate circuits (28). Each multiply/accumulate circuit (28) includes a parallel/serial arrangement of multiple multiplier/accumulators (84) interconnected with weight storage elements (80) to yield multiple neural weightings and sums in a single clock cycle. A neural processing language is used to program the neural engine (20) through a conventional host personal computer (22). The parallel processing permits very high processing speeds to permit real-time pattern classification capability.

Abstract: First and second passive sensors (14,16), which may be mounted on different earth orbiting satellites, provide relative azimuth and elevation coordinates to sensed objects (A,B,C) such as hostile missiles. Minimum and maximum possible ranges to the objects (A,B,C) along lines-of-sight (18a,18b,18c) from the first sensor (14) are predetermined, and used to calculate "range lines" (24,26,28) which are coincident with the lines-of-sight (18a,18b,18c) and extend from the respective minimum to maximum ranges respectively. The range lines (24,26,28) are transformed into the field of view of the second sensor (16), and matched to the azimuth and elevation coordinates of the respective objects (A,B,C) using a basic feasible solution (greedy) or global optimization algorithm.