Spaceborne memory organization, phase 1 Final report

Application of associative memories to data processing for future space vehicle

A ferrofluid based neural network: design of an analogue associative memory

We analyse an associative memory based on a ferrofluid, consisting of a system of magnetic nano-particles suspended in a carrier fluid of variable viscosity subject to patterns of magnetic fields from an array of input and output magnetic pads. The association relies on forming patterns in the ferrofluid during a trainingdphase, in which the magnetic dipoles are free to move and rotate to minimize the total energy of the system. Once equilibrated in energy for a given input-output magnetic field pattern-pair the particles are fully or partially immobilized by cooling the carrier liquid. Thus produced particle distributions control the memory states, which are read out magnetically using spin-valve sensors incorporated in the output pads. The actual memory consists of spin distributions that is dynamic in nature, realized only in response to the input patterns that the system has been trained for. Two training algorithms for storing multiple patterns are investigated. Using Monte Carlo simulations of the physical system we demonstrate that the device is capable of storing and recalling two sets of images, each with an accuracy approaching 100%.Comment: submitted to Neural Network

Memory formation in matter

Memory formation in matter is a theme of broad intellectual relevance; it sits at the interdisciplinary crossroads of physics, biology, chemistry, and computer science. Memory connotes the ability to encode, access, and erase signatures of past history in the state of a system. Once the system has completely relaxed to thermal equilibrium, it is no longer able to recall aspects of its evolution. Memory of initial conditions or previous training protocols will be lost. Thus many forms of memory are intrinsically tied to far-from-equilibrium behavior and to transient response to a perturbation. This general behavior arises in diverse contexts in condensed matter physics and materials: phase change memory, shape memory, echoes, memory effects in glasses, return-point memory in disordered magnets, as well as related contexts in computer science. Yet, as opposed to the situation in biology, there is currently no common categorization and description of the memory behavior that appears to be prevalent throughout condensed-matter systems. Here we focus on material memories. We will describe the basic phenomenology of a few of the known behaviors that can be understood as constituting a memory. We hope that this will be a guide towards developing the unifying conceptual underpinnings for a broad understanding of memory effects that appear in materials

Engineering study for a mass memory system for advanced spacecrafts Final report, 1 Dec. 1969 - 1 Jul. 1970

Mass memory system for advanced spacecraf

Spaceborne memory organization - Appendices Interim report

Computational requirements and information storage devices for unmanned spacecraft in advanced planetary exploration, 1975 - 198

Interference filters as nonlinear decision-making elements for three-spot pattern recognition and associative memories

Simple patterns consisting of three spots (V and Γ) have been recognized by dividing, shifting, and recombining beams onto bistable ZnS interference filters. This experiment demonstrates AND-gate operation, cascading, and a moderate amount of parallelism, but a laser power of several watts was required and the response times were several milliseconds. An associative memory for fingerprint identification has been constructed using a VanderLugt correlator and an interference filter as a reflective thresholding device

Data storage hierarchy systems for data base computers.

Thesis. 1979. Ph.D.--Massachusetts Institute of Technology. Alfred P. Sloan School of Management.MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY.Vita.Bibliography: p. 241-248.Ph.D