This paper presents a few of the OSU-Stillwater Power engineering Laboratory capabilities. Digital signal acquisition and virtual instrumentation (National Instruments' LABVIEW software) are used to help students ...
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This paper presents a few of the OSU-Stillwater Power engineering Laboratory capabilities. Digital signal acquisition and virtual instrumentation (National Instruments' LABVIEW software) are used to help students understand the concepts by visualizing the data. Some features of virtual instrumentation are real-time display of waveforms, phasor diagrams, real and reactive power, spectral analysis as well as the ability to interpret the data graphically. Some techniques for improved laboratory practice as well as the laboratory capabilities concerning experiments of transformers and rotating machines are presented.
The ability to execute a program in reverse is advantageous for shortening debug time. This paper presents a reverse execution methodology at the assembly instruction-level with low memory and time overheads. The core...
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The ability to execute a program in reverse is advantageous for shortening debug time. This paper presents a reverse execution methodology at the assembly instruction-level with low memory and time overheads. The core idea of this approach is to generate a reverse program able to undo, in almost all cases, normal forward execution of an assembly instruction in the program being debugged. The methodology has been implemented on a PowerPC processor in a custom made debugger. Compared to previous work - all of which use a variety of state saving techniques - the experimental results show 2.5X to 400X memory overhead reduction for the tested benchmarks. Furthermore, the results with the same benchmarks show an average of *** to 5.7X time overhead reduction.
This paper proposes techniques used in finding a power system operating point that is both economically optimal and stable in the small-signal sense. To make the system small-signal stable, we should choose a power sy...
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This paper proposes techniques used in finding a power system operating point that is both economically optimal and stable in the small-signal sense. To make the system small-signal stable, we should choose a power system operating point such that changes in system state variables due to small disturbances die out quickly. Thus, we need to know how changes in the power system operating point affect the linearized system's eigenvalues, i.e. the eigenvalue sensitivities. Methods to compute eigenvalue and eigenvector sensitivities are discussed.
In this paper, we describe a simple technique involving indirect negative feedback that extends the useable common-mode input-voltage range of the MOS differential pair by a saturation voltage. In this method, we use ...
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In this paper, we describe a simple technique involving indirect negative feedback that extends the useable common-mode input-voltage range of the MOS differential pair by a saturation voltage. In this method, we use a replica differential pair to sense when the bias transistor supplying the tail current falls out of saturation. We then set the bias voltage so that the sum of the two differential-pair output currents is equal to the bias current. We present experimental results from a version of the differential pair that was fabricated in a 0.5-μ.m CMOS process along with a comparison with an identical differential pair with a fixed bias with respect to their common-mode input ranges.
Symbol-by-symbol detection is often used in systems with interleaved coded modulation in order to provide the needed soft-decision metrics for the decoding of the outer code. This paper develops a suboptimal symbol-by...
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Symbol-by-symbol detection is often used in systems with interleaved coded modulation in order to provide the needed soft-decision metrics for the decoding of the outer code. This paper develops a suboptimal symbol-by-symbol detection method for the demodulation of continuous phase modulated (CPM) signals. The proposed algorithm offers a reduced-complexity symbol-by-symbol detection in which the numbers of matched filters and trellis states are appreciably reduced. The complexity reduction is achieved by approximating the CPM signal using the Laurent representation. An accompanying simulation study shows that the performance degradation relative to the optimal full complexity algorithm is small for a variety of CPM signals. Index Terms-Continuous phase modulation, Laurent decomposition, complexity reduction, symbol-by-symbol detection.
To perform accurate AOA (angle of arrival) estimations using the MUSIC (Multiple Signal Classification) algorithm, accurate antenna array calibration data must be available. Since it is not feasible to store calibrati...
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To perform accurate AOA (angle of arrival) estimations using the MUSIC (Multiple Signal Classification) algorithm, accurate antenna array calibration data must be available. Since it is not feasible to store calibration data for all possible AOAs, developing continuous functions to represent the calibration data is an attractive alternative. Neural networks are effective for estimating functions, and are very applicable for this situation. Two different iterative training methods for modular networks are presented and compared. The first method employs a fixed section size and variable network size, and the second method employs a variable section size and a fixed network sized.
In this paper, we present preamble and receiver design for a Q transmit L receive multi input multi output OFDM system. Tasks performed by the receiver are synchronization in time and frequency domains, followed by ch...
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In this paper, we present preamble and receiver design for a Q transmit L receive multi input multi output OFDM system. Tasks performed by the receiver are synchronization in time and frequency domains, followed by channel estimation and noise variance estimation. An algorithm is developed such that only Q OFDM symbols of a generalized length are required to perform functions of the preamble. Coarse time synchronization is performed using inherent periodicity in the preamble. Frequency offset estimation is then performed in the time domain, followed by residual frequency offset estimation in the frequency domain followed by fine time synchronization. The channel estimation algorithm is developed using least squares principle. Simulations are carried out for a broadband fixed wireless access scenario using a preamble with and without zero-padding of tones in the frequency domain.
A very simple LMS-based adaptive notch filter implemented in FPGAís can be used for carrier recovery of an Octaphase shift-keying signal. The key aspect of our paper lies in the alternative approach in the realiz...
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A very simple LMS-based adaptive notch filter implemented in FPGAís can be used for carrier recovery of an Octaphase shift-keying signal. The key aspect of our paper lies in the alternative approach in the realization of carrier frequency detection or synchronization circuit. The carrier frequency after detection is used in the conventional Octaphase shift-keying detector. Also the demodulator has a simple hardware realization that does not require a reference signal.
The tuning of the band pass filter in the simple heterodyne filter structure can be done over a range of 90-degrees by changing the heterodyne frequency. However in this, the heterodyne frequency is constant and can b...
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The tuning of the band pass filter in the simple heterodyne filter structure can be done over a range of 90-degrees by changing the heterodyne frequency. However in this, the heterodyne frequency is constant and can be made adaptive by introducing a Numerical Controlled Oscillator. The proposed design structure uses the Numerical Controlled Oscillator output that can be used as the heterodyne frequency so as to tune the band pass filter effectively.
We present and evaluate a novel implemented approach for learning to recognize events in video. First, we introduce a sublanguage of event logic, called k-AMA, that is sufficiently expressive to represent visual event...
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We present and evaluate a novel implemented approach for learning to recognize events in video. First, we introduce a sublanguage of event logic, called k-AMA, that is sufficiently expressive to represent visual events yet sufficiently restrictive to support learning. Second, we develop a specific-to-general learning algorithm for learning event definitions in k-AMA. Finally, we apply this algorithm to the task of learning event definitions from video and show that it yields definitions that are competitive with hand-coded ones.
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