Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 18 of 18 for “"error feedback"”.
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An improved Pi-Sigma neural network using error feedback for time series prediction
… Order Neural Network (HONN) using recurrent feedback appeared as a powerful technique in the domain of time series prediction and it has the ability to expand the input space, making them more efficient for solving complex problems and perform high learning abilities in time series …
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Visuomotor adaptation in older adults with and without cognitive impairment
… to carry out tasks encountered in daily living. Error-driven learning processes are believed to be central to visuomotor adaptation. Research has shown that increasing error feedback may enhance adaptation in neurologically damaged participants. Some literature on dementia and motor learning has …
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Anger and denial as predictors of cardiovascular reactivity in women
… three counterbalanced conditions: (1) no feedback, (2) error feedback without observer present, (3) error feedback with observer present. As hypothesized, women who reported a high level of denial and a low level of anger exhibited reliably greater systolic blood pressure to the …
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Development of a Variational Part Model Using In-Process Dimensional Measurement Error
… of CNC machined parts, dynamic machining errors due to on-line disturbances (tool deflection, tool wear, heat deformation, etc.) should be accounted for in some manner. Unless these on-line disturbances are properly handled, it is obvious that a high degree of geometric accuracy is …
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Recurrent error-based ridge polynomial neural networks for time series forecasting
… time series. Moving-average (MA) inputs (i.e., errors) however have not adequately considered. The use of MA inputs, which can be done by feeding back forecasting errors as extra network inputs, alongside AR inputs help to produce more accurate forecasts. Among numerous existing NNs …
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Optimality and iterative learning control: duality and input prediction
… are made by eliminating an explicit current-error feedback loop and providing the facility of both current error feedback, and previous error feedforward within the control structure. This, in turn, with the case when either state-feedback or output-feedback is used to solve the ILC control …
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EFFECTIVE TRAINING OF NEURAL NETWORKS FOR BETTER GENERALIZATION
… Shampoo using 4-bit Cholesky quantization with error feedback, enabling scalable second-order training. From the data side, we investigate why data-centric strategies enhance generalization. We analyze semi-supervised learning and data augmentation through the lens of feature learning, …
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Depressive Feedback Utilization: The Feedback-Related Negativity as an Index of the`Catastrophic Response to Perceived Failure'
… current research examined the impact of negative feedback on event-related potentials associated with error detection and correction in individuals with varying levels of depression. Depression is known to be associated with a number of cognitive effects, including deficits in executive …
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Radar tracking system development
… range. From these tracks it then produces angle-error feedback signals that command the IH gimbals, keeping targets centered along the antenna boresight. Over three years, a new Seeker Computer was built to replace an old system constrained by obsolete hardware. The redevelopment project was a …
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Model-following control applications to nonlinear mechanical systems
… conditions are presented and the resulting error dynamics are given. The stability of error dynamics is ensured, using Liapunov's second theorem; by modifying the model state rates, which effectively introduces error feedback. The methodology is applied to two problems. Motion control of an …
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Switching control systems and their design automation via genetic algorithms
… In the field of fuzzy logic control (FLC) using error feedback variables there are two main problems. The first is the poor transient response (jerking) encountered by the conventional 2-dimensional rule-base fuzzy PI controller. Secondly, conventional 3-D rule-base fuzzy PID control design is …
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Representation and Interaction of Sensorimotor Learning Processes
… consecutively, in the following phase of clamped error feedback, the expression of adaptation spontaneously rotated from the direction of the second force field, towards the direction of the first force field. Finally, we examined the interaction of sensorimotor memories formed based on separate …
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Robust Parameter Design for Automatically Controlled Systems and Nanostructure Synthesis
… controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the …
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Insight Driven Sampling for Interactive Data Intensive Computing
… computing. However, sampling introduces error. The objective of sampling is to reduce the amount of data being processed without introducing too much error into the results of the data intensive application. To determine an adequate level of sampling one can use statistical measures like …
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Bridge to digital converters for environmental monitoring in edge IoT devices
… converter (BDC) that utilizes an error-feedback modulator DAC, providing a low-area alternative to the traditional binary weighted approach. The BDC occupies 0.01 mm2 area, and consumes 7.4 μW with a 45 ms conversion time. It achieves 9.1 ENOB for a DC input and a Walden FoM of …
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Design of Active Clamp for Fast Transient Voltage Regulator-Down (VRD) Applications
… the slow compensation and slow slew rate of the error amplifier. So the voltage drop is still quite large. Comparing with traditional linear controlled switching regulator such as voltage control and current control buck converter, active clamp has a lot of the advantages for the transient …
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Controlled particle systems for nonlinear filtering and global optimization
… problem, the main contribution is to extend the feedback particle filter (FPF) algorithm to connected matrix Lie groups. In its general form, the FPF is shown to provide an intrinsic coordinate-free description of the filter that automatically satisfies the manifold constraint. The properties of …
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CodeLens: A generative ai framework for dynamic feedback on SQL semantic errors
This Thesis was approved for publication on 2024-12-06 at 16:45.