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Related Concept Videos

Generator Voltage Control01:21

Generator Voltage Control

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Generator voltage control is crucial for maintaining the stable operation of synchronous generators and wind turbines. In older models, a DC generator driven by the rotor delivers DC power to the rotor's field winding, and the power is transferred through slip rings and brushes. In the latest models, static or brushless exciters are used. Static exciters rectify AC power from the generator terminals and then transfer the DC power directly to the rotor. Brushless exciters, on the other hand, use...
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Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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An alternator converts mechanical energy into electrical energy that varies sinusoidally, resulting in AC current. Meanwhile, a DC generator converts mechanical energy into electrical energy, which are DC pulses with the same polarity. The construction of a DC generator is similar to that of an alternator, except that the pair of slip rings is replaced by a single split ring, also called a commutator. The commutator functions like a periodic rotary switch; it changes the contacts with the...
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Electric Generator: Alternator01:25

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Electric generators induce an emf by rotating a coil in a magnetic field. A simple alternator is an AC generator that creates electrical energy that varies sinusoidally with time. A simple alternator consists of a conducting loop that is placed inside a uniform magnetic field. The loop is connected to split rings connected to the external circuit with the help of brushes.
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Van de Graaff Generator01:15

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Van de Graaff generators (or Van de Graaffs) are devices used to demonstrate high voltage due to static electricity that can also be used for research. Robert Van de Graaff first built one in 1931 (based on original suggestions by Lord Kelvin) for use in nuclear physics research.
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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Related Experiment Video

Updated: Dec 29, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

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A Style-Based Generator Architecture for Generative Adversarial Networks.

Tero Karras, Samuli Laine, Timo Aila

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |February 4, 2020
    PubMed
    Summary
    This summary is machine-generated.

    We introduce a novel generator architecture for generative adversarial networks (GANs) that enables unsupervised separation of image attributes and intuitive control. This new approach improves image quality and disentanglement, with new methods to quantify these improvements.

    Related Experiment Videos

    Last Updated: Dec 29, 2025

    Generating Strictly Controlled Stimuli for Figure Recognition Experiments
    05:39

    Generating Strictly Controlled Stimuli for Figure Recognition Experiments

    Published on: March 18, 2019

    5.5K

    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Generative Adversarial Networks (GANs) are powerful tools for image generation.
    • Existing GAN architectures often struggle with disentangling high-level attributes and controlling specific variations.
    • Style transfer techniques offer potential for improved GAN architectures.

    Purpose of the Study:

    • To propose a novel generator architecture for GANs inspired by style transfer.
    • To achieve unsupervised separation of high-level attributes and stochastic variations in generated images.
    • To enable intuitive, scale-specific control over image synthesis.

    Main Methods:

    • Developed an alternative generator architecture for GANs, incorporating principles from style transfer.
    • Trained the architecture on a new, high-quality dataset of human faces.
    • Introduced two new automated methods for quantifying interpolation quality and disentanglement.

    Main Results:

    • The proposed architecture achieves automatic, unsupervised separation of attributes like pose and identity.
    • It allows for intuitive, scale-specific control over image synthesis.
    • The generator improves state-of-the-art distribution quality metrics and disentanglement.

    Conclusions:

    • The novel GAN generator architecture offers improved control and disentanglement.
    • New quantification methods provide reliable metrics for evaluating GAN performance.
    • The study contributes a valuable new dataset for face generation research.