Displaying 337 resources
Certification Certification
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Orthogonal Signal Transforms. Fourier Series

This lecture overviews Orthogonal Signal Transforms. Fourier Series that has many applications in signal processing, analysis and compression.

Category
Data for AI, Recommendations towards policy changes
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Fourier Transform

This lecture overviews the topics of continuous-time periodic signals, signal frequencies and Fourier Transform (FT).  Its relation to Laplace transform is presented.

Category
Data for AI, Recommendations towards policy changes
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Discrete-time Signals and Systems

This lecture overviews discrete-time Signals and Systems topics. Discrete-time signals are presented: periodic signals, delta signal, unit step signal, exponential signal, trigonometric signals, complex exponential signal.

Category
Data for AI, Recommendations towards policy changes
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

UAV Infrastructure Inspection

This lecture overviews the use of drones for infrastructure inspection and maintenance. Various types of inspection, e.g., using visual cameras, LIDAR or thermal cameras are reviewed. Primary application area is electric line inspection.

Category
Recommendations towards policy changes
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Autonomous Underwater Vessel Sensors

This lecture overviews Autonomous Underwater Vessel Perception that has many applications in Autonomous Underwater Vessel missions.

Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Mathematical brain modeling

This lecture overviews Mathematical Brain Modeling that has many applications in Artificial Neural Networks.  It covers the following topics in detail: Brain Cells (Sensory and Motor neurons, Interneurons, glia).

Category
Data for AI, Systems, methodologies, hardware, and tools
Source
AI-OnDemand