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.
Results
Showing 1 to 20 of 493 for “"Transformers"”.
-
Measurement and modelling of errors for relaying current transformers and voltage transformers
… developed to estimate errors in relaying current transformers and voltage transformers. The tool has been developed to collect data in a substation and send it to a remote location over a telephone line. Different schemes were evaluated and tested in the laboratory. The final choice was made on …
-
Efficiency of alternate current transformers
Thesis: B.S., Massachusetts Institute of Technology, Department of Electrical Engineering, 1891
-
Sketch Quality Prediction Using Transformers
The quality of an input sketch can affect performance of the computational algorithms. However, the quality of a sketch is not often considered when working with sketch tasks and automated sketch quality prediction has not been previously studied. This thesis presents quality prediction on the …
-
Structural Self-Supervised Objectives for Transformers
In this Thesis, we leverage unsupervised raw data to develop more efficient pre-training objectives and self-supervised tasks that align well with downstream applications. In the first part, we present three alternative objectives to BERT’s Masked Language Modeling (MLM), namely Random Token …
-
State transformers and modes of computation
State transformers, which form the objects in a subequalizing category, are a generalization of the transition functions of automata. The 2-categorical properties of subequalizers are developed and related to adjunctions in a 2-category. A calculus of monads in a 2-category is presented, and …
-
An investigation of type H transformers
Thesis: B.S., Massachusetts Institute of Technology, Department of Electrical Engineering, 1903
-
Adapting Transformers for Structured Data Domains
… to enhance the adaptability and effectiveness of Transformers in structured data domains beyond their traditional use in natural language processing (NLP). We revisit key elements of the transformer framework - including input representations, attention formulations, auxiliary tasks, prediction …
-
Wideband high-power transmission line pulse transformers
Geometric transformers are often used in radar and communications systems to transition between signal driving and radiating elements that terminate in significantly different geometries with unity input/output impedance. This work demonstrates the design and construction process of a geometric …
-
Meta-Learning Exploration Strategies with Decision Transformers
… learning and sequence-modeling capabilities of transformers, combined with supervised learning and deep reinforcement learning techniques to learn exploration strategies directly from experience. Through extensive experiments on synthetic and semi-synthetic exploration tasks, we demonstrate that …
-
Searching for Efficient Multi-Stage Vision Transformers
Vision Transformer (ViT) demonstrates that Transformer for natural language processing can be applied to image classification tasks and result in comparable performance to convolutional neural networks (CNN), which have been studied in computer vision for years. This naturally raises the question …
-
First principles design of coreless power transformers
… novel 4-coil high frequency coreless power transformers from first principles via lumped equivalent circuit models. The procedure is applied to construct a design for 100W transformer with an S21 parameter value of .96. Using MATLAB and LTspice, simulation tools have been developed to …
-
Failure detection in transformers using vibrational analysis
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1986.
-
Synthesizing Tabular Time Series Data using Transformers
Using synthetic data in place of real data can come with numerous benefits, such as the protection of privacy. However, synthesizing tabular data is difficult, since it is heterogeneous and might contain relationships between its columns and between its rows. While there has been much work …
-
Current Sharing Method for DC-DC Transformers
An ever present trend in the power conversion industry is to get higher performance at a lower cost. In a computer server system, the front-end converter, supplying the load subsystems, is typically a multiple output power supply. The power supply unit is custom designed and its output voltages are …
-
Impact of Geomagnetically Induced Currents on Power Transformers
… Geomagnetically Induced Current (GIC) on power transformers in electrical power systems. A simulator to calculate the flows of GIC in an electrical power network, based on an assumed or measured induced geoelectric potential is proposed. This simulator includes all needed mapping techniques to …
-
Investigation of increasing fault Gas in excitation transformers
… in oil insulation in three similar excitation transformers in Tanjung Bin Power Plant; Transformer A, Transformer B, and Transformer C. The research covers the transformer oil sample collection, and the experiment of Dissolved Gas Analysis (DGA) in laboratory. Then, the DGA results as raw data …
-
On the Synthesis of Passive Networks without Transformers
This thesis is concerned with the synthesis of passive networks, motivated by the recent invention of a new mechanical component, the inerter, which establishes a direct analogy between mechanical and electrical networks. We investigate the minimum numbers of inductors, capacitors and resistors …
-
Evaluating transformers as memory systems in reinforcement learning
… reinforcement learning, however, the success of transformers in natural language processing tasks has highlighted a promising and viable alternative. Memory in reinforcement learning is particularly difficult as rewards are often sparse and distributed over many time steps. Early research into …
-
Benchmarking Graph Transformers Toward Scalability for Large Graphs
Graph transformers (GTs) have gained popularity as an alternative to graph neural networks (GNNs) for deep learning on graph-structured data. In particular, the self-attention mechanism of GTs mitigates the fundamental limitations of over-squashing, over-smoothing, and limited expressiveness that …
-
Transformers as Empirical Bayes Estimators The Poisson Model
We study the ability of transformers to perform In Context Learning (ICL) in the setting of Empirical Bayes for the Poison Model. On the theoretical side, we demonstrate the expressibility of transformers by formulating a way to approximate the Robbins estimator, the first empirical Bayes estimator …
Page 1 of 25