Dynamic program.ing (DP) is a principled way to design optimal controllers for certain classes of nonlinear systems;unfortunately, DP is computationally very expensive. The Reinforcement Learning methods known as Adap...
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Dynamic program.ing (DP) is a principled way to design optimal controllers for certain classes of nonlinear systems;unfortunately, DP is computationally very expensive. The Reinforcement Learning methods known as Adaptive Critics (AC) provide computationally feasible means for performing approximate Dynamic program.ing (ADP). The term 'adaptive ' in A C refers to the critic 's improved estimations of the Value Function used by DP. To apply DP, the user must craft a Utility function that embodies all the problem-specific design specifications/criteria. Model Reference Adaptive Control methods have been successfully used in the control community to effect on-line redesign of a controller in response to variations in plant parameters, with the idea that the resulting closed loop system dynamics will mimic those of a Reference Model. The work reported here 1) uses a reference model in ADP as the key information input to the Utility function, and 2) uses ADP off-line to design the desired controller. Future work will extend this to on-line application. This method is demonstrated for a hypersonic shaped airplane called LoFL YTE®;its handling characteristics are natively a little "hotter" than a pilot would desire. A control augmentation subsystem is designed using ADP to make the plane "feel like " a better behaved one, as specified by a Reference Model. The number of inputs to the successfully designed controller are among the largest seen in the literature to date.
In 1960, Campbell derived a quantity that he defined as the coefficient rate of a random process that involves the process spectral entropy. However, no potential applications of the coefficient rate were identified. ...
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The Xilinx University program.is supported by a comprehensive web resource developed and maintained by students at the department of electrical and computerengineering at Michigan State University. The site is design...
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Estimation of volume, surface area, area, length and number in stereology is based on a manual count of the number of intersections between the feature of interest and a specific low-resolution geometrical test probe....
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Estimation of volume, surface area, area, length and number in stereology is based on a manual count of the number of intersections between the feature of interest and a specific low-resolution geometrical test probe. It is usually a tedious and imprecise process, hut benefits from the user's ability to identify the feature of interest. In computer-based stereology, by contrast, a high-resolution test probe is used, generally yielding greater precision but suffering from imperfection of the automated classification. The trade-offs between manual and computer-based stereology are introduced and the conditions under which each is advantageous are defined.
Estimation of volume or the ratio of volumes in an image requires both mensuration and classification. The former is achieved through stereology - a set of techniques that estimate such parameters as area, volume, sur...
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Estimation of volume or the ratio of volumes in an image requires both mensuration and classification. The former is achieved through stereology - a set of techniques that estimate such parameters as area, volume, surface area, length, and number. Classification is achieved by extracting features that capture discriminating information (e.g., about tissue type). Both stereology and classification can be performed either manually or by computer. Manual techniques for the combination are based on coarse point counting (low resolution), but assumed perfect pixel classification. computer-based methods, on the other hand, rely on very fine point counting but in general suffer from imperfect pixel classification. This paper examines the interaction between manual and image processing-based approaches; in particular, we present a measure that combines the classification and measurement errors. Estimation of the variance is used to define the conditions under which each method is and is not advantageous despite its underlying error. This allows the user to choose a method that optimizes overall performance, given the human and machine capabilities available. Illustrations are given of cases in which each method can be preferable, as measured by the variance of the estimate of the performance that was inferred from the measurement.
The use of multiple antennas at both the transmitter and receiver can significantly increase the channel capacity. These systems are called the multiple-input multiple-output (MIMO) systems. By using orthogonal freque...
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The use of multiple antennas at both the transmitter and receiver can significantly increase the channel capacity. These systems are called the multiple-input multiple-output (MIMO) systems. By using orthogonal frequency division multiplexing (OFDM) transmission techniques, the MIMO-OFDM system can achieve high spectral efficiency, which makes it an attractive candidate for high-data-rate wireless applications. In this paper, we propose a convolutionally coded MIMO-OFDM system with EM-based channel estimation and a QRD-M data detection algorithm. In our systems, one training symbol is transmitted from each transmit antenna for the MEMO channel estimation at the receiver. With the channel estimates available, we apply the QRD-M algorithm on the estimated channel matrix for suboptimal data detection with reasonable computational cost. The bit error rate (BER) and packet error rate (PER) performance of the MIMO-OFDM systems are compared. In the simulations, the bit error rate performance of our systems is 9 (or 5) dB better than that of uncoded (or coded) BLAST systems.
We investigate the issues in voice communications using IP over tandem connections of wireline and wireless links with the goal of determining end-to-end system performance. We study the particular example of using G....
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We investigate the issues in voice communications using IP over tandem connections of wireline and wireless links with the goal of determining end-to-end system performance. We study the particular example of using G.711 speech coding in the backbone wireline network and adaptive multi-rate (AMR) speech coding in a wireless LAN tandem network and study the impact of specific methods of adaptive re-encoding, error concealment, error control coding, and network protocol design to deliver the desired end-to-end quality of service. In addition to simulation results and objective speech quality measures, we present estimation-theoretic and information-theoretic analyses for the tandem packet loss link connections.
An artificial neural network (ANN)-based approach to pharmacodynamic population analysis presented. In pursuit of an optimal and cost-effective strategy for drug dosing in patients with renal failure, an ANN is applie...
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An artificial neural network (ANN)-based approach to pharmacodynamic population analysis presented. In pursuit of an optimal and cost-effective strategy for drug dosing in patients with renal failure, an ANN is applied to perform drug-dose-effect modeling. Such a model allows for versatile prediction of the response to the drug at the effect site and, subsequently, for adjusting the dosing regimen.
In this article, we show that a code division multiple access (CDMA) system employing long codes can be interpreted as a multiple input multiple output system where the transmit filters are time-varying. We derive con...
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In this article, we show that a code division multiple access (CDMA) system employing long codes can be interpreted as a multiple input multiple output system where the transmit filters are time-varying. We derive conditions for existence of zero-forcing equalizers and verify through simulations that these conditions are useful guidelines for the design of appropriate solution in the presence of noise. Compared to similar works in the literature, the derived conditions allow a reduction in the length of the equalizer filters, while imposing no constraints on the channel order.
The use of multiple antennas at both the transmitter and receiver can significantly increase the channel capacity. These systems are called the multiple-input multiple-output (MIMO) systems. By using orthogonal freque...
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The use of multiple antennas at both the transmitter and receiver can significantly increase the channel capacity. These systems are called the multiple-input multiple-output (MIMO) systems. By using orthogonal frequency division multiplexing (OFDM) transmission techniques, the MIMO-OFDM system can achieve high spectral efficiency, which makes it an attractive candidate for high-data-rate wireless applications. In this paper, we propose a convolutionally coded MIMO-OFDM system with EM-based channel estimation and a QRD-M data detection algorithm. In our systems, one training symbol is transmitted from each transmit antenna for the MIMO channel estimation at the receiver. With the channel estimates available, we apply the QRD-M algorithm on the estimated channel matrix for suboptimal data detection with reasonable computational cost. The bit error rate (BER) and packet error rate (PER) performance of the MIMO-OFDM systems are compared. In the simulations, the bit error rate performance of our systems is 9 (or 5) dB better than that of uncoded (or coded) BLAST systems.
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