PPT-Signal processing and Networking for Big Data

Applications Lecture 3 Block Structured Optimization for Big Data Optimization Zhu Han University of Houston Thanks for Dr Mingyi Hongs slides 1 Outline Chapter 3334 Block Structured Problems. Decimation or downsampling reduces the sampling rate whereas expansion or upsampling fol lowed by interpolation increases the sampling rate Some applications of multirate signal processing are Upsampling ie increasing the sampling frequency before D project Guitar Effects. Joshua “Rock Star” Jenkins . Jeff “Tremolo” Smith . Jairo. “the boss” Rojas. Table of contents. Typical Guitar Effects Pipeline.. Classifying Effects for guitar implementation.. Jayanthi. . Sivaswamy. . and. . Suryakanth. V . Gangashetty. 2. Broad Areas of . Signal . Processing . Activities. Audio, speech and language . Medical image processing . Computer vision (image and video). Tata Institute of Fundamental Research, Mumbai. Contact: bsn@tifr.res.in. Signal Processing Electronics. B.Satyanarayana, TIFR, Mumbai Signal Processing Electronics SERCEHEP11, VECC, Kolkata. CSIRO Astronomy and space science. John Tuthill . | Digital Systems Engineer. 25 September 2012. Star-on Machine. Dr. Seuss - The . Sneetches. and Other Stories. Outline. What is “back-end signal processing”. Applications. Lecture . 6: . Optimize Finite Sum. Zhu Han. University of Houston. Thanks Dr. . Mingyi. Hong slides. 1. Outline (Chapter 10). Problem Formulation. Algorithms. The SAG and SAGA algorithm [Le Roux 12][. Applications. Lectures 11-12: Deep Learning Basics. Zhu Han. University of Houston. Thanks for Dr. . Hien. Nguyen slides and help by . Xunshen. Du and Kevin Tsai. 1. outline. Motivation and overview. Lecture . 10: . Sublinear. Algorithm. Zhu Han. University of Houston. Thanks for Professor Dan Wang’s slides. 1. outline. Motivations. Inequalities and classifications . Examples. Applications. 2. Applications. Lectures 12-13: . Regularization and Optimization. Zhu Han. University of Houston. Thanks . Xusheng. Du and Kevin Tsai For Slide Preparation. 1. Part 1 Regularization Outline. Parameter Norm Penalties. Applications. Lecture . 21: . Tensor Basics. Zhu Han. University of Houston. Thanks for Dr. Hung Nguyen’s Slides. 1. Outline. 1. Basic concepts. 2. Tensor operations. 3. Tensor analysis. 4. Applications. Lecture . 10: . Sublinear. Algorithm. Zhu Han. University of Houston. Thanks for Professor Dan Wang’s slides. 1. outline. Motivations. Inequalities and classifications . Examples. Applications. 2. Applications. Lecture . 2: . Preliminary Review. Zhu Han. University of Houston. 1. outline. Convex . optimization (thanks for Dr. . Mingyi. Hong’s slides). Convex Optimization. Gradient descent and Newton methods. 2 recent HHT software implementation. Description of HHT Technology HHT-based processing consists of two main elements: Empirical Mode Decomposition (EMD), and Hilbert spectral analysis. The EMD phase Jayanthi. . Sivaswamy. . and. . Suryakanth. V . Gangashetty. 2. Broad Areas of . Signal . Processing . Activities. Audio, speech and language . Medical image processing . Computer vision (image and video).