A method and apparatus for coding and decoding a sequence of data packets with use of a novel class of forward error correcting codes having coding rates greater than 1/2 which nonetheless provide relatively high levels of channel protection against burst erasures with a relatively low decoding delay. In accordance with certain illustrative encoder embodiments of the present invention, the source information contained in each of a plurality of packets to be coded is similarly divided into a plurality of (similar) corresponding portions, and âchecksumsâ are computed over multiple data packets, each such checksum being based on different (i. e. , non-corresponding) portions of at least two of the multiple packets. These âchecksumsâ are then advantageously appended to various subsequent data packets to be coded. By using different portions of multiple packets from which the checksums are computed, forward error correcting codes having rates greater than 1/2 which provide high levels of channel protection against burst erasures with relatively low decoding delays are advantageously provided.
Quantizing Signals Using Sparse Generator Factor Graph Codes
Jonathan S. Yedidia - Cambridge MA Emin Martinian - Arlington MA
Assignee:
Mitsubishi Electric Research Laboratories, Inc. - Cambridge MA
International Classification:
H03M 700
US Classification:
341107, 714751, 714752, 714794
Abstract:
A method quantizes an input signal of N samples into a string of k symbols drawn from a q-ary alphabet. A complementary method reproduces a minimally distorted version of the input signal from the quantized string, given some distortion measure. First, an [N,k] linear error-correcting code that has a sparse generator factor graph representation is selected. A fixed mapping from q-ary symbols to samples is selected. A soft-input decoder and an encoder for the SGFG codes is selected. A cost function is determined from the input signal and a distortion measure, using the fixed mapping. The decoder determines an information block corresponding to a code word of the SGFG code with a low cost for the input signal. The input signal can be reproduced using the encoder for the SGFG code, in combination with the fixed mapping.
Apparatus And Method For Adaptive, Multimode Decoding
Emin Martinian - Medford MA, US Carl-Erik W. Sundberg - Chatham NJ, US
International Classification:
H03M 13/00 H03M 13/03
US Classification:
714761, 714787
Abstract:
The present invention provides for adaptive and multimode decoding, in a data packet-based communication system, to provide improved received signal quality in the presence of burst erasures or random bit errors, with particular suitability for real-time, delay sensitive applications, such as voice over Internet Protocol. In the presence of burst erasures, the adaptive multimode decoder of the present invention provides burst erasure correction decoding, preferably utilizes a maximally short (MS) burst erasure correcting code, which has a comparatively short decoding delay. Depending upon the level of such burst erasures, different rate MS codes may be utilized, or other codes may be utilized, such as hybrid or multidescriptive codes. When no burst erasures are detected, the adaptive multimode decoder of the present invention provides random bit error correction decoding, in lieu of or in addition to corresponding burst erasure correction coding.
Lossy Data Compression Exploiting Distortion Side Information
Emin Martinian - Arlington MA, US Gregory W. Wornell - Wellesley MA, US Ram Zamir - Tel Aviv, IL
Assignee:
Massachusetts Institute of Technology - Cambridge MA
International Classification:
H03M 7/30
US Classification:
341 51, 341 87, 37524002
Abstract:
Described are techniques for performing lossy encoding. Source data and quality data are received by an encoder. The encoder maps the source data into a compressed representation having a level of distortion in accordance with the quality information. The compressed representation may be decoded without using the quality information.
Method And System For Determining Unwrapped Phases From Noisy Two-Dimensional Wrapped-Phase Images
Jonathan Yedidia - Cambridge MA, US Ali Azarbayejani - Boston MA, US Emin Martinian - Waltham MA, US
Assignee:
Mitsubishi Electric Research Laboratories, Inc. - Cambridge MA
International Classification:
G01S 13/90
US Classification:
342 25R, 342 25 A, 342 25 C, 342 25 F, 342195
Abstract:
A method converts an input image of noisy wrapped phases to an output image of absolute unwrapped phases. The noisy wrapped phases in the input image are represented as a set of re-wrapped phases and a set of phase shifts. The set of re-wrapped phases are partitioned into a first group and a second group. Integer differences between the phase shifts are optimized while holding the re-wrapped phases fixed. Then, the first group of re-wrapped phases are optimized, while holding the integer differences between the phase shifts, and the second group of re-wrapped phases fixed. The integer differences between the phase shifts are optimized again, while holding the re-wrapped phases fixed. Then, the second group of re-wrapped phases are optimized, while holding the integer differences between the phase shifts, and the first group of re-wrapped phases fixed. The optimizing steps are repeated until the re-wrapped phase converge. Then, the converged re-wrapped phases and integer differences between the phase shifts are output as an output image of absolute unwrapped phases.
Jun Xin - Quincy MA, US Emin Martinian - Arlington MA, US Anthony Vetro - Cambridge MA, US
Assignee:
Mitsubishi Electric Research Laboratories, Inc. - Cambridge MA
International Classification:
H04N 5/225
US Classification:
3482181
Abstract:
A method decomposes multiview video acquired of a scene by multiple cameras. Each multiview video includes a sequence of frames, and each camera provides a different view of the scene. A prediction mode is selected from a temporal prediction mode, a spatial prediction mode, and a view interpolation prediction mode. The multiview videos are then decomposed into low band frames, high band frames, and side information according to the selected prediction mode.
Method And System For Managing Reference Pictures In Multiview Videos
Jun Xin - Quincy MA, US Emin Martinian - Waltham MA, US Alexander Behrens - Bueckeburg, DE Anthony Vetro - Arlington MA, US Huifang Sun - Billerica MA, US
Assignee:
Mitsubishi Electric Research Laboratories, Inc. - Cambridge MA
International Classification:
H04N 5/225
US Classification:
3482181
Abstract:
A system and method manages multiview videos. A reference picture list is maintained for each current frame of multiple multiview videos. The reference picture list indexes temporal reference pictures, spatial reference pictures and synthesized reference pictures of the multiview videos. Then, each current frame of the multiview videos is predicted according to reference pictures indexed by the associated reference picture list during encoding and decoding.
Biometric Based User Authentication And Data Encryption
Anthony Vetro - Arlington MA, US Jonathan S. Yedidia - Cambridge MA, US Emin Martinian - Arlington MA, US Sergey M. Yekhanin - Cambridge MA, US
Assignee:
Mitsubishi Electric Research Laboratories, Inc. - Cambridge MA
International Classification:
G06F 9/46 G06F 21/00
US Classification:
713186, 382115
Abstract:
First biometric parameters are acquired from a user. Input data are encrypted according to the biometric parameters to produce ciphertext. The biometric parameters are encoded using a syndrome encoder to produce a syndrome code. The ciphertext and the syndrome code are associated with each other and stored in a computer readable media so that only the same user can subsequently decrypt the cipher text.
Massachusetts Institute of Technology 1998 - 2004
Doctorates, Doctor of Philosophy
Skills:
Computer Science Statistics Hedge Funds Macroeconomics Investments Equities Machine Learning Algorithms Matlab Signal Processing C++ Python Programming Data Analysis
Googleplus
Emin Martinian
Lived:
Arlington, Massachusetts
Work:
Bain Capital - Investment Professional at Global Macro Hedge Fund
Education:
Sunny Hills High School, University of California at Berkeley (BS), Massachusetts Insitute of Technology (PhD)
About:
Emin Martinian earned a B.S. from UC Berkeley in 1997, and an S.M and Ph.D. from MIT in 2000 and 2004 (all in electrical engineering and computer science). Emin has been awarded a National Science Fou...
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