In digital signal processing, downsampling, compression, and decimation are terms associated with the process of resampling in a multi-rate digital signal processing system. Both downsampling and decimation can be synonymous with compression, or they can describe an entire process of bandwidth reduction (filtering) and sample-rate reduction. When the process is performed on a sequence of samples of a signal or a continuous function, it produces an approximation of the sequence that would have been obtained by sampling the signal at a lower rate (or density, as in the case of a photograph). Decimation is a term that historically means the removal of every tenth one. But in signal processing, decimation by a factor of 10 actually means keeping only every tenth sample. This factor multiplies the sampling interval or, equivalently, divides the sampling rate. For example, if compact disc audio at 44,100 samples/second is decimated by a factor of 5/4, the resulting sample rate is 35,280. A system component that performs decimation is called a decimator. Decimation by an integer factor is also called compression. (Wikipedia).
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Frequency domain analysis of downsampling a discrete-time signal (decreasing the effective sampling rate) by lowpass filtering followed by discardin
From playlist Sampling and Reconstruction of Signals
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Frequency domain analysis of upsampling a discrete-time signal (increasing the effective sampling rate) by inserting zeros followed by lowpass filte
From playlist Sampling and Reconstruction of Signals
Upsampling and Downsampling Example
http://AllSignalProcessing.com for more great signal processing content, including problems with solutions, concept/screenshot files, quizzes, MATLAB and data files. An example of upsampling and downsampling in a digital filtering problem, tracking the DTFT and FT of the signals after ea
From playlist Sampling and Reconstruction of Signals
Introduction to Signal Processing
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. Introductory overview of the field of signal processing: signals, signal processing and applications, phi
From playlist Introduction and Background
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
Determining Signal Similarities
Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Find a signal of interest within another signal, and align signals by determining the delay between them using Signal Processing Toolbox™. For more on Signal Processing To
From playlist Signal Processing and Communications
Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Remove an unwanted tone from a signal, and compensate for the delay introduced in the process using Signal Processing Toolbox™. For more on Signal Processing Toolbox, visi
From playlist Signal Processing and Communications
Post-analysis temporal downsampling
Are your time-frequency results matrices too big? Watch this video to learn how to reduce the temporal resolution of your results to match their temporal precision, which can save lots of time and space. The video uses files you can download from https://github.com/mikexcohen/ANTS_youtube
From playlist OLD ANTS #5) Normalization and time-frequency post-processing
Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Learn how to smooth your signal using a moving average filter and Savitzky-Golay filter using Signal Processing Toolbox™. For more on Signal Processing Toolbox, visit: htt
From playlist Signal Processing and Communications
Lecture 5 | Convolutional Neural Networks
In Lecture 5 we move from fully-connected neural networks to convolutional neural networks. We discuss some of the key historical milestones in the development of convolutional networks, including the perceptron, the neocognitron, LeNet, and AlexNet. We introduce convolution, pooling, and
From playlist Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Introduces three pervasive problems in signal processing: filtering, equalization, and system identification.
From playlist Introduction and Background
Beating Nyquist with Compressed Sensing, in Python
This video shows how it is possible to beat the Nyquist sampling rate with compressed sensing (code in Python). Book Website: http://databookuw.com Book PDF: http://databookuw.com/databook.pdf These lectures follow Chapter 3 from: "Data-Driven Science and Engineering: Machine Learning,
From playlist Sparsity and Compression [Data-Driven Science and Engineering]
Nicki Holighaus: Time-frequency frames and applications to audio analysis - Part 1
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Analysis and its Applications
Processing Megapixel Images with Deep Attention-Sampling Models
Current CNNs have to downsample large images before processing them, which can lose a lot of detail information. This paper proposes attention sampling, which learns to selectively process parts of any large image in full resolution, while discarding uninteresting bits. This leads to enorm
From playlist Deep Learning Architectures
Temporal resolution vs. precision, pre- and post-convolution
This video lesson is part of a complete course on neuroscience time series analyses. The full course includes - over 47 hours of video instruction - lots and lots of MATLAB exercises and problem sets - access to a dedicated Q&A forum. You can find out more here: https://www.udemy.
From playlist NEW ANTS #3) Time-frequency analysis
The Unreasonable Effectiveness of JPEG: A Signal Processing Approach
Visit https://brilliant.org/Reducible/ to get started learning STEM for free, and the first 200 people will get 20% off their annual premium subscription. Chapters: 00:00 Introducing JPEG and RGB Representation 2:15 Lossy Compression 3:41 What information can we get rid of? 4:36 Introduc
From playlist Fourier
Quantization and Coding in A/D Conversion
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Real sampling systems use a limited number of bits to represent the samples of the signal, resulting in quantization of the signal amplitude t
From playlist Sampling and Reconstruction of Signals