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The Fu Foundation School of Engineering and Applied Science Department of Electrical Engineering COLUMBIA UN IVERSITY IN TH E CITY OF N EW YORK Signal and Information Processing Prof. John Wright

SIGNAL AND INFORMATION PROCESSING Faculty Shih-Fu Chang Multimedia Dan Ellis Music and audio analysis John Paisley Bayesian nonparametrics Xiaodong Wang Communications, genomic signal processing John Wright High-dimensional data, images Many faculty have connections, e.g., Dimitris Anastassiou Computational Biology, Javad Lavaei optimization for power networks, Nima Mesgarani neural signal processing, Aurel Lazar neuroengineering

SIP Course Sequences If this is hard to read, see the web version Red: Fall 2014

E4810 Digital Signal Processing Prof. John Wright, Mondays and Wednesdays, 10:10-11:25 Digital filtering in time and frequency domain Discrete-time signals and systems, sampling theory, transform analysis, system structures, IIR and FIR filter design Discrete Fourier Transform, Fast Fourier Transforms.

E6860 Advanced Digital Signal Processing Prof. T. Nguyen, Fridays 10:10-12:40 Multirate and multidimensional signal processing. Short-time Fourier transform, signal expansion in discrete/continuous time. Filter banks, multiresolution analysis, wavelets. Applications to image compression and understanding.

E4650 Convex Optimization Prof. Javad Lavaei, Mondays 10:10-12:40 Theory, algorithms and engineering applications of convex optimization. Theory of convex sets and functions. Numerical algorithms. Applications in circuits, communications, control, signal processing, power.

ELEN E4750 Fall 2014 Thursdays 1:10pm-3:40pm E4750 Signal Processing on Mobile Multicore Platforms ing and Prof. Communications Zoran Kostic, Tuesdays on Mobile 1:10-3:40 Multicore (Applications of Parallel Computing) en to SEAS Students interested in systems skills in el computing, importance to mobile unications industry in the licable to research projects of CU EE/CS faculty. Methods for deploying signal processing and communications algorithms on ile processors with heterogeneous computing infrastructures consisting of a pose, graphics and digital signal processors. Using programming languages d CUDA for computational speedup in audio, image and video processing l data analysis. Significant design project. Deploying signal processing and communications algorithms on contemporary mobile processors Signal processing with heterogeneous computing infrastructures consisting of general purpose, graphics and digital signal processors 172 (at) columbia.edu urse Link Programming languages such as OpenCL and CUDA for computational gains eering Department Project/applications in audio, image and video processing and computational data analysis. 1

E6873 Detection and Estimation Prof. Ta-Hsin Li, Tuesdays 7-9:30 PM Fundamentals of detection and estimation theory. Hypothesis testing, signal detection, parameter estimation, signal estimation, and selected advanced topics. Suitable for students in communications, control, signal processing, and related areas.

E6601 Introduction to Control Theory Prof. Richard Longman, Wednesdays 7-9:30 PM Introduction to classical and modern feedback control (graduate level). Scalar and matrix differential equation models. Transfer functions, block diagram manipulations, closed-loop response. Proportional, rate, and integral controllers, and compensators. Design by root locus and frequency response. Controllability, observability. Luenberger observers, pole placement, and linear-quadratic cost controllers.

E6893 Topics in Info Processing: Big Data Analytics Prof. C. Y. Lin, Thursdays 7-9:30 PM Analyzing Big Data: from acquisition and storage to processing Platforms, including Hadoop, Spark Uploading, distribute, and processing data, including HDFS, HBase, KV stores, document database, and graph database Large-scale machine learning for big data

Special topics (688X): ELEN E6880 Topic: Space-Time Coding / SP Wireless Comm. (Sp. 08, 07) ELEN E6880 Topic: MIMO Wireless Communication (Spring 13, 12, 11) ELEN E6881 Topic: Video Coding and Communications (Spring 09, 08) ELEN E6882 Topic: Stat. Methods for Video Index & Analysis (Fall 07) ELEN E6882 Topic: Visual Search Engine (Spring 12, 11) ELEN E6883 Topic: Detection & Estimation (Fall 10, 09, 08, 06) ELEN E6884 Topic: Speech Recognition (Fall 05) ELEN E6884 Topic: Data Compression (Spring 13, 12, 11) ELEN E6885 Topic: Network Science (Fall 13, 12, 11, 10) ELEN E6886 Topic: Multimedia Security Systems (Spring 06) ELEN E6886 Topic: Sparse Rep. / High Dim. Geometry (Fall 12, 11) ELEN E6887 Topic: Statistical Learning Theory (Spring 10, 09) ELEN E6888 Topic: Intro. to LTE & WiMax Systems (Spring 13, 12, 11, 10) ELEN E6889 Topic: Distributed Stream Processing and Analysis (Spring 10) EECS E6890 Topic: Visual Recognition and Search (Spring 13) EECS E6891 Topic: Replicating Computational Results (Spring 13) EECS E6898 Topic: From Data to Solutions (Fall 13, 12)

Related course offerings (coding, communications, ect.) ELEN 4702 Digital Communications ELEN 6718 Algebraic Coding Theory ELEN 6761 Computer Communications Networks ELEN 6770 Topics: Next Generation Networks ELEN 6773 Topics: Network Economics and Engineering ELEN 6776 Topics: Content Distribution Networks ELEN 6881 Topics in Signal Processing: Multicarrier Resource Allocation ELEN 6920 Topics in VLSI: VLSI for Signal Processing ELEN 6950 Wireless and Mobile Networking

Frequently asked questions: Should I take DSP (4810) or Advanced DSP (6860)? What about machine learning? One likely topics course for Sp. 15 Sparse Representation + High-Dimensional Geometry (Wright) Plus additional topics offerings How can I get involved in research in SIP?