Concept

Σ-finite measure

Related MOOCs (14)

Basic signal processing concepts, Fourier analysis and filters. This module can be used as a starting point or a basic refresher in elementary DSP

Digital Signal Processing II

Adaptive signal processing, A/D and D/A. This module provides the basic tools for adaptive filtering and a solid mathematical framework for sampling and quantization

Digital Signal Processing III

Advanced topics: this module covers real-time audio processing (with examples on a hardware board), image processing and communication system design.

Digital Signal Processing IV

Advanced topics: this module covers real-time audio processing (with examples on a hardware board), image processing and communication system design.

Introduction to optimization on smooth manifolds: first order methods

Learn to optimize on smooth, nonlinear spaces: Join us to build your foundations (starting at "what is a manifold?") and confidently implement your first algorithm (Riemannian gradient descent).

Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.

Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.

Neuronal Dynamics - Computational Neuroscience of Single Neurons

The activity of neurons in the brain and the code used by these neurons is described by mathematical neuron models at different levels of detail.

Neuronal Dynamics - Computational Neuroscience of Single Neurons

The activity of neurons in the brain and the code used by these neurons is described by mathematical neuron models at different levels of detail.

Neuro Robotics

At the same time, several different tutorials on available data and data tools, such as those from the Allen Institute for Brain Science, provide you with in-depth knowledge on brain atlases, gene exp

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Digital Signal Processing I

Basic signal processing concepts, Fourier analysis and filters. This module can be used as a starting point or a basic refresher in elementary DSP

Digital Signal Processing II

Adaptive signal processing, A/D and D/A. This module provides the basic tools for adaptive filtering and a solid mathematical framework for sampling and quantization

Digital Signal Processing III

Advanced topics: this module covers real-time audio processing (with examples on a hardware board), image processing and communication system design.

Digital Signal Processing IV

Advanced topics: this module covers real-time audio processing (with examples on a hardware board), image processing and communication system design.

Introduction to optimization on smooth manifolds: first order methods

Learn to optimize on smooth, nonlinear spaces: Join us to build your foundations (starting at "what is a manifold?") and confidently implement your first algorithm (Riemannian gradient descent).

Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.

Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.

Neuronal Dynamics - Computational Neuroscience of Single Neurons

The activity of neurons in the brain and the code used by these neurons is described by mathematical neuron models at different levels of detail.

Neuronal Dynamics - Computational Neuroscience of Single Neurons

The activity of neurons in the brain and the code used by these neurons is described by mathematical neuron models at different levels of detail.

Neuro Robotics