The property inheritance network (PIN) is a dynamically controlled machine that accesses information stored in a hierarchical content addressable memory. The associative memory is implemented using adaptive resonance ...
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The property inheritance network (PIN) is a dynamically controlled machine that accesses information stored in a hierarchical content addressable memory. The associative memory is implemented using adaptive resonance circuits. These circuits are monitored by a set of control neurons that become active when certain system states occur and generate signals that control a sequential search through a taxonomy of stored information. This paper reviews pertinent knowledge representation concepts and summarizes the adaptive resonance theory of Carpenter and Grossberg as it applies to the PIN. The PIN architecture and control implementation are presented and simulation results are discussed.
A computer method for determining the scattering, absorption, and internal field structure of thin flat disks of arbitrary refractive index is described. The code is shown to be accurate for all angles of incidence fo...
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A computer method for determining the scattering, absorption, and internal field structure of thin flat disks of arbitrary refractive index is described. The code is shown to be accurate for all angles of incidence for radii up to at least two free space wavelengths and for media ranging from pure dielectric to highly conductive ones. The accuracy of the method is assessed by comparison with published experimental data and with results computed by other methods. The applicability of this technique for analyzing clouds of disk-shaped aerosols is also discussed.
An efficient 3-D object-centered knowledge base is described. The ability to on-line generate a 2-D image projection or range image for any object/viewer orientation from this knowledge base is addressed. Applications...
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An efficient 3-D object-centered knowledge base is described. The ability to on-line generate a 2-D image projection or range image for any object/viewer orientation from this knowledge base is addressed. Applications of this knowledge base in associative processors and symbolic correlators are then discussed. Initial test results are presented for a multiple degree of freedom object recognition problem. These include new techniques to achieve object orientation information and two new associative memory matrix formulations.
Research into two-dimensional phase unwrapping has uncovered interesting and troublesome inconsistencies that cause path-dependent results. Cellular automata, which are simple, discrete mathematical systems, offered p...
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Research into two-dimensional phase unwrapping has uncovered interesting and troublesome inconsistencies that cause path-dependent results. Cellular automata, which are simple, discrete mathematical systems, offered promise of computation in a nondirectional, parallel manner. A cellular automaton was discovered that can unwrap consistent phase data in n dimensions in a path-independent manner and can automatically accommodate noise-induced (pointlike) inconsistencies and arbitrary boundary conditions (region partitioning). For data with regional (nonpointlike) inconsistencies, no phase-unwrapping algorithm will converge, including the cellular-automata approach. However, the automata method permits more simple visualization of the regional inconsistencies. Examples of its behavior on one- and two-dimensional data are presented.
The exact-image method, recently introduced for the solution of electromagnetic field problems involving sources above a planar interface between two homogeneous media, is shown to be valid also for sources located in...
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The exact-image method, recently introduced for the solution of electromagnetic field problems involving sources above a planar interface between two homogeneous media, is shown to be valid also for sources located in complex space, which makes its application possible for Gaussian-beam analysis. It is demonstrated that the Goos–H?nchen shift and the angular shift of a TE-polarized beam are correctly given as asymptotic results by the exact-reflection-image theory. Also, the apparent-image location giving the correct Gaussian beam transmitted through the interface is obtained as another asymptotic check. The theory described here makes it possible to calculate the exact coupling from the Gaussian beam to the reflected and refracted beams as well as to the surface wave.
This paper reviews two custom electronic circuits that implement some simple models of neural function. The circuits include a thin-film array of read-only resistive synapses and an array of programmable synapses and ...
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This paper reviews two custom electronic circuits that implement some simple models of neural function. The circuits include a thin-film array of read-only resistive synapses and an array of programmable synapses and amplifiers serving as electronic neurons. Circuit performance and architecture are discussed.
The symmetry theorems on the complete forward and backward scattering Mueller matrices for light scattering from a single dielectric scatterer (as opposed to an ensemble of scatterers) are systematically and thoroughl...
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The symmetry theorems on the complete forward and backward scattering Mueller matrices for light scattering from a single dielectric scatterer (as opposed to an ensemble of scatterers) are systematically and thoroughly analyzed. Symmetry operations considered include discrete rotations about the incident direction and mirror planes not coinciding with the scattering plane. For forward scattering we find sixteen different symmetry shapes (not including the totally asymmetric one), which may be classified into five symmetry classes, with identical reductions in the forward scattering matrices for all symmetry shapes that fall into the same symmetry class. For backward scattering we find only four different symmetry shapes, which may be classified into only two symmetry classes. The forward scattering symmetry theorems also lead to a symmetry theorem on the total extinction cross section. Based on the conclusions of this work it should be possible to design quick and nondestructive methods for the identification of certain small objects, when suitable partial information about the objects to be identified is already available. A promising practical example is given.
We describe a computational method of determining the optical constants n(λ),k(λ) and the film thickness d from photometric R(λ),T(λ) and ellipsometric Ψ(λ),Δ(λ) data. Combinations of three or four of the meas...
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We describe a computational method of determining the optical constants n(λ),k(λ) and the film thickness d from photometric R(λ),T(λ) and ellipsometric Ψ(λ),Δ(λ) data. Combinations of three or four of the measured quantities are compared using Newton-Raphson and Simplex techniques. The method is applied to thin films of gold and amorphous metallic alloys. The results are discussed.
The perception of an unchanging surface color under different illuminations requires the computation of the scene-illuminant color either directly or indirectly. A possible source for the computation is the specular h...
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The perception of an unchanging surface color under different illuminations requires the computation of the scene-illuminant color either directly or indirectly. A possible source for the computation is the specular highlight of the surface reflection. Some issues related to color constancy are discussed, and a theory for computing the scene-illuminant chromaticity from specular highlight is described. An interesting result of the theory is that in an ideal situation, two surfaces of different colors will be sufficient for the computation.
Human and machine visual sensing is enhanced when surface properties of objects in scenes, including color, can be reliably estimated despite changes in the ambient lighting conditions. We describe a computational met...
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Human and machine visual sensing is enhanced when surface properties of objects in scenes, including color, can be reliably estimated despite changes in the ambient lighting conditions. We describe a computational method for estimating surface spectral reflectance when the spectral power distribution of the ambient light is not known.
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