Reconstruction and the Sampling Theorem
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Analysis of the conditions under which a continuous-time signal can be reconstructed from its samples, including ideal bandlimited interpolati
From playlist Sampling and Reconstruction of Signals
From playlist filter (less comfortable)
Frequency Domain Interpretation of Sampling
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Analysis of the effect of sampling a continuous-time signal in the frequency domain through use of the Fourier transform.
From playlist Sampling and Reconstruction of Signals
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Practical requirements for an analog anti-aliasing filter to bandlimit continuous-time signals before sampling.
From playlist Sampling and Reconstruction of Signals
Practical DSP and Oversampling
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Limitations of analog anti-aliasing and anti-imaging filters motivate a practical digital filtering approach in which high rates are used for sampli
From playlist Sampling and Reconstruction of Signals
Practical Reconstruction - The Zero-Order Hold
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Practical reconstruction of continuous-time signals from sampling using the zero-order hold and analog anti-imaging filtering.
From playlist Sampling and Reconstruction of Signals
Introduction to Frequency Selective Filtering
http://AllSignalProcessing.com for free e-book on frequency relationships and more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Separation of signals based on frequency content using lowpass, highpass, bandpass, etc filters. Filter g
From playlist Introduction to Filter Design
Lecture 17, Interpolation | MIT RES.6.007 Signals and Systems, Spring 2011
Lecture 17, Interpolation Instructor: Alan V. Oppenheim View the complete course: http://ocw.mit.edu/RES-6.007S11 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT RES.6.007 Signals and Systems, 1987
Equivalent Analog Filtering (c)
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Studies the equivalent analog filter corresponding to sampling a signal, applying a discrete-time filter, and reconstructing a continuous-time signa
From playlist Sampling and Reconstruction of Signals
Rob Fergus: "Deep Learning Methods for Vision, Pt. 2"
Graduate Summer School 2012: Deep Learning, Feature Learning "Deep Learning Methods for Vision, Pt. 2" Rob Fergus, New York University Institute for Pure and Applied Mathematics, UCLA July 12, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-schools/graduate-summer-s
From playlist GSS2012: Deep Learning, Feature Learning
reaLD 3D glasses filter with a linear polarising filter
This is for a post on my blog: http://blog.stevemould.com
From playlist Everything in chronological order
Stanford CS230: Deep Learning | Autumn 2018 | Lecture 7 - Interpretability of Neural Network
Andrew Ng, Adjunct Professor & Kian Katanforoosh, Lecturer - Stanford University http://onlinehub.stanford.edu/ Andrew Ng Adjunct Professor, Computer Science Kian Katanforoosh Lecturer, Computer Science To follow along with the course schedule and syllabus, visit: http://cs230.stanfo
From playlist Stanford CS230: Deep Learning | Autumn 2018
Holographic Tomography | MIT 2.71 Optics, Spring 2009
Holographic Tomography Instructor: Aditya Bhakta, Danny Codd View the complete course: http://ocw.mit.edu/2-71S09 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 2.71 Optics, Spring 2009
A discrete signal has to be reconstructed to get back into the continuous domain.
From playlist Discrete
Deep Learning Course Purdue University Fall 2016 http://e-lab.github.io///html/teaching-bme595a-deep-learning.html
From playlist Deep-Learning-Course
Lecture 16, Sampling | MIT RES.6.007 Signals and Systems, Spring 2011
Lecture 16, Sampling Instructor: Alan V. Oppenheim View the complete course: http://ocw.mit.edu/RES-6.007S11 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT RES.6.007 Signals and Systems, 1987