Abstract: An architecture and process are provided that encodes information into a cellular automata memory structure such that it can be recalled utilizing unique memory anchors (engrams) in a manner that both identifies and relates each piece of information relative to other data points. The automata may be individually programmable with a limited, local ruleset that activates other cellular automata based on prior patterns that were fed into the array. Deep Learning Neural Network (DLNN) systems may be probed to understand what discriminators are being used to classify the data, which is not possible with conventional DLNN techniques.

Abstract: An image detection assembly includes a light source that is configured to generate at least one pulsed light beam. A modulator is configured to direct the pulsed light beam onto a device via a plurality of light patterns such that a plurality of electrical signals are generated by the device. Each electrical signal corresponds to a different light pattern. A signal processing apparatus is coupled to the device and the signal processing apparatus is configured to receive the electrical signals and to digitize each electrical signal to record a plurality of signal vectors such that each signal vector corresponds to a different electrical signal. The signal processing apparatus is also configured to generate at least one image output based, at least in part, on the recorded signal vectors and the light patterns such that the image output enables a determination of at least one transient effect on the device.