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Spike Response Model (SRM)
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Related lectures (55)
Spectral Estimation Methods
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Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.
Convolutional Neural Networks: Filters and Channels
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Explores weight sharing, filters, channels, and data augmentation in convolutional neural networks.
Electrical Metrology
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Explores electrical metrology, covering random variables, noise sources, and their impact on electronic devices.
Noise in Devices and Circuits
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Explores different types of noise in devices and circuits, including interference noise, inherent noise, and random signals.
Noise and Measurements
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Explores electronic, thermomechanical, and amplifier noise, calibration of amplitude, frequency tracking, and system limits.
Image Processing: Enhancement and Analysis
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Explores image processing techniques such as contrast manipulation, enhancement, and sharpening using Fiji software.
Sparse Regression
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Covers the concept of sparse regression and the use of Gaussian additive noise in the context of MAP estimator and regularization.
Electrical Metrology: Noise Reduction Techniques
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Explores noise reduction techniques in electrical metrology, covering properties of charge, current, voltage, noise sources, and filtering methods.
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.
Small Signal Analysis: High-Speed Photodetectors
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Discusses the small signal analysis of high-speed photodetectors, focusing on circuit components, noise analysis, and modeling for receiver systems.
Gaussian Mixture Models & Noisy Signals
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Explores Gaussian mixture models and denoising noisy signals using a probabilistic approach.
Operational Amplifiers: Noise Analysis
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Explores noise analysis in operational amplifiers and strategies for noise reduction.
Understanding Ideal Detectors: Theory and Applications
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Provides an overview of ideal detectors, focusing on their theory, noise limitations, and performance metrics in optical detection systems.
Noise Analysis in Optical Detectors: Key Examples
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Covers examples of noise in optical detectors, including avalanche photodiodes and fluorescence correlation spectroscopy.
Data-Driven Modeling in Neuroscience: Meenakshi Khosla
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By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Ideal Detectors: Characteristics and Applications
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Covers the characteristics and applications of ideal detectors in optical detection, focusing on photonic and thermal detectors.
Q Factor and BER Analysis
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Explores the analysis of the Q factor and Bit Error Rate in photonic systems.
Biophysical Understanding of Neuronal Behavior
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Explores the biophysical understanding of neuronal behavior, focusing on action potentials, neuron modeling challenges, and dendritic inhibition.
Extreme Value Analysis: Threshold Selection
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Discusses threshold selection in extreme value analysis and its impact on model performance.
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.
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