Engineering topics
Publications and source records attributed to Ochoa, Ellen.
Networks of higher order have enhanced capabilities to distinguish between different two-dimensional patterns and to recognize those patterns. Also enhanced capabilities to "learn" patterns to be recognized: "trained" with far fewer examples and, therefore, in less time than necessary to train comparable first-order neural networks.
Experiments demonstrated feasibility of synthetic-discriminant-function filter encoded in binary spatial light modulator. Filter is part of optoelectronic apparatus indicating degree of correlation between input image and any number of training images of same object at various positions and orientations. Used in optical correlator to recognize rotated images, or in tracking system to recognize moving vehicle or other substantially rigid object from any direction.
Experimental results are presented which demonstrate that effective binary synthetic discriminant functions (SDFs) can be constructed if the binary nature of the filter modulation is included in SDF synthesis. It is also shown that the iterative procedure needed to produce the SDF is well performed on the optical correlator, as opposed to off-line computation. Binary SDF filters have been demonstrated which produce approximately equal correlation peaks over in-plane rotation ranges up to 75 deg and out-of-plane rotation ranges up to 60 deg. This technique, combined with the translational position invariance of optical filters, allows a single filter to track a Shuttle Orbiter as it moves along a curved path across the input field.
The Photonic Processing group is engaged in applied research on optical processors in support of the Ames vision to lead the development of autonomous intelligent systems. Optical processors, in conjunction with numeric and symbolic processors, are needed to provide the powerful processing capability that is required for many future agency missions. The research program emphasizes application of analog optical processing, where free-space propagation between components allows natural implementations of algorithms requiring a large degree of parallel computation. Special consideration is given in the Ames program to the integration of optical processors into larger, heterogeneous computational systems. Demonstration of the effective integration of optical processors within a broader knowledge-based system is essential to evaluate their potential for dependable operation in an autonomous environment such as space. The Ames Photonics program is currently addressing several areas of interest. One of the efforts is to develop an optical correlator system with two programmable spatial light modulators (SLMs) to perform distortion invariant pattern recognition. Another area of research is optical neural networks, also for use in distortion-invariant pattern recognition.
The development status of optical processing techniques under development at NASA-JPL, NASA-Ames, and NASA-Johnson, is evaluated with a view to their potential applications in future NASA planetary exploration missions. It is projected that such optical processing systems can yield major reductions in mass, volume, and power requirements relative to exclusively electronic systems of comparable processing capabilities. Attention is given to high-order neural networks for distortion-invariant classification and pattern recognition, multispectral imaging using an acoustooptic tunable filter, and an optical matrix processor for control problems.