Further evaluation of the constrained least squares electromagnetic compensation method

Technologies exist for construction of antennas with adaptive surfaces that can compensate for many of the larger distortions caused by thermal and gravitational forces. However, as the frequency and size of reflectors increase, the subtle surface errors become significant and degrade the overall electromagnetic performance. Electromagnetic (EM) compensation through an adaptive feed array offers means for mitigation of surface distortion effects. Implementation of EM compensation is investigated with the measured surface errors of the NASA 15 meter hoop/column reflector antenna. Computer simulations are presented for: (1) a hybrid EM compensation technique, and (2) evaluating the performance of a given EM compensation method when implemented with discretized weights

Asset Pricing With Multiplicative Habit and Power-Expo Preferences (Subsequently published in "Economics Letters", 2007, 94(3), 319-325. )

Multiplicative habit introduces an additional consumption risk as a determinant of equity premium, and allows time preference and habit strength, in addition to risk aversion, to affect "price of risk". A model combining multiplicative habit and power-expo preferences cannot be rejected.

Fertility, Volatility, and Growth

Empirically, growth rates are negatively correlated with birth rates; they are also correlated with production risk. We argue that these stylized facts are related, and arise jointly from the decision of how many children to have in a risky economic environment.stochastic growth; fertility; volatility

"Asset Pricing With Multiplicative Habit and Power-Expo Preferences"

Multiplicative habit introduces an additional consumption risk as a determinant of equity premium, and allows time preference and habit strength, in addition to risk aversion, to affect "price of risk". A model combining multiplicative habit and power-expo preferences cannot be rejected.

An application of foraminiferal ecology Vicinity of Horn Island, Mississippi

Foraminifera were examined in 159 samples cut from 23 piston c ores collected in the vicinity of Horn Island, Mississippi. The age of the oldest marine sediment cored is approximately 5000 years . The following data on depositional surface Foraminifera were determined and compared with those data from reports on similar areas: (a) specific composition, (b) percentage of arenaceous Foraminifera, (c) numbers of species, (d) specific dominance, and (e) numbers of specimens. These date show that environments of core samples can be determined by their foraminiferal content and such interpretation utilized to reconstruct the depositional history of an area. A non-marine clay and sand existed in the area at a time when sea level was lower. As sea level rose, nearshore marine deposition occurred in the present open-gulf area . Alternating brackish and near-marine conditions existed in the present Sound area. A barrier island system, established early in the period of core sediment deposition, offered varying degrees of resistance to the invasion of marine waters. As deposition continued, a "near-delta" influence was impressed upon the area. This influence existed throughout most of the depositional period. At present, a brackish environment exists north of Horn Island and a marine environment occurs south of the island. Mixing of these environments occurs in the passe s on each end of Horn Island. The island acts as a barrier to marine water, and brackish water from the Sound now dilutes the open gulf to a greater extent than in t he past. The "near-delta" influence is now negligible

The Spirit of Capitalism and Excess Smoothness

In a recent paper [Luo, Smith, and Zou (2009)] we showed that the spirit of capitalism could in theory resolve the two fundamental anomalies of modern consumption theory, excess sensitivity and excess smoothness. However, that basic model could not plausibly explain the empirical magnitude of excess smoothness. In this paper we develop two extensions of the model ¡ª one with transitory and permanent shocks to income, the other with a stochastic interest rate ¡ª that where the spirit of capitalism can explain excess smoothness.The spirit of capitalism, Consumption smoothing, Interest rate risk

Antenna analysis using neural networks

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern shaping. The interesting thing about D-C synthesis is that the side lobes have the same amplitude. Five-element arrays were used. Again, 41 pattern samples were used for the input. Nine actual D-C patterns ranging from -10 dB to -30 dB side lobe levels were used to train the network. A comparison between simulated and actual D-C techniques for a pattern with -22 dB side lobe level is shown. The goal for this research was to evaluate the performance of neural network computing with antennas. Future applications will employ the backpropagation training algorithm to drastically reduce the computational complexity involved in performing EM compensation for surface errors in large space reflector antennas