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Lecture
Comparison of Noise Models
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Related lectures (50)
Escape noise
MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons
Explores escape noise in computational neuroscience, covering stochastic intensity, interspike intervals, likelihood functions, noise model comparison, and rate versus temporal codes.
Scientific Computing in Neuroscience
Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.
Neuronal Dynamics: Random Networks
MOOC: Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition
Explores the dynamics of neuronal populations, emphasizing random networks and mean-field arguments for connectivity.
Neural Signals and Signal Processing: Modeling and Simulation
Covers the fundamentals of neural signals and signal processing, focusing on modeling and simulation of neural systems.
From diffusive noise to escape noise
MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons
Compares diffusive noise and escape noise in neuronal dynamics, focusing on simulation and calculation complexity.
Membrane potential fluctuations
MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons
Explores stochastic spike arrival and membrane potential fluctuations in single neurons.
Quality of Integrate-and-Fire Models
MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons
Explores the quality of Integrate-and-Fire models in computational neuroscience through comparisons with experimental data and mathematical predictions.
Spike Response Model (SRM)
MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons
Covers the Spike Response Model (SRM) in computational neuroscience and its relation to the adaptive leaky integrate-and-fire model.
Electrical Metrology
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Explores electrical metrology, covering random variables, noise sources, and their impact on electronic devices.
Noise and Measurements
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Explores electronic, thermomechanical, and amplifier noise, calibration of amplitude, frequency tracking, and system limits.
Electrical Metrology
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Explores different types of noise in electrical systems and their impact on electronic devices.
Noise Reduction Techniques in Analog Circuits
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Explores noise and offset reduction techniques in analog circuits, focusing on Autozero and Chopper Stabilization.
Network Simulation and Activity Dynamics
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Explores neural network simulation, activity dynamics, and validation processes to ensure accurate predictions.
Noise in Electronics
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Introduces the fundamentals of noise in electronics, covering origins, signal types, power characteristics, and noise sources.
Noise in Electronics: Fundamentals and Applications
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Explores noise in electronics, covering average power, signal-to-noise ratio, deterministic and random signals, and noise amplification.
Supervised Learning Essentials
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Introduces the basics of supervised learning, focusing on logistic regression, linear classification, and likelihood maximization.
EKV Charge-based Model: Transistor Design
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Explores the EKV charge-based model for low-voltage and low-power circuit design, emphasizing transistor characteristics and noise models.
Scientific Computing in Neuroscience
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Explores scientific computing in neuroscience, emphasizing the simulation of neurons and networks using tools like NEURON, NEST, and BRIAN.
Physical Noise Analysis: High-Speed Photodetectors
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Covers the physical noise analysis in high-speed photodetectors, focusing on signal-to-noise ratios and various noise sources affecting performance.
Strategies to Combat Noise Sources
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Covers strategies to combat noise sources in electronics measurements and explores techniques to mitigate noise and improve measurement accuracy.
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