Methods and apparatus to perform frequency-domain equalization in high-speed downlink packet access (HSDPA) receivers for wireless channels with large delay-spreads are disclosed. An example method comprises computing a first frequency-domain equalizer (FDE) coefficient for a first set of multipaths, computing a second FDE coefficient for a second set of multipaths, computing a first equalized signal by equalizing a received code division multiple access (CDMA) signal with the first FDE coefficient, computing a second equalized signal by equalizing the received CDMA signal with the second FDE coefficient, delaying the first equalized signal by a delay difference between the first and the second sets, and combining the delayed first equalized signal and the second equalized signal.
Automatic Learning Of Logos For Visual Recognition
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatically extracting logos from images. Methods include generating a query list including a plurality of logo search queries, for each logo search query of the plurality of logo search queries: generating a plurality of image search results, each image search result including image data, and clustering the plurality of image search results into a plurality of clusters, each cluster including a plurality of images of the plurality of image search results, extracting, for each cluster of the plurality of clusters, a representative image to provide a plurality of representative images, and a name corresponding to the representative image to provide a plurality of names, and providing the plurality of representative images and the plurality of names to a logo index, the logo index being accessible to identify one or more logo images in a query image.
Systems And Methods For Parallel Dual-Mode Turbo Decoders
Tao Zhang - San Diego CA, US Jianbin Zhu - Poway CA, US Yuan Li - San Diego CA, US
Assignee:
Mindspeed Technologies, Inc. - Newport Beach CA
International Classification:
H03M 13/00
US Classification:
714755, 714752, 714758, 714759, 714780
Abstract:
According to some embodiments, a turbo decoder configured for High-Speed Packet Access (HSPA) and Long Term Evolution (LTE) is provided, comprising: a plurality of maximum a posteriori (MAP) engines; a plurality of extrinsic memory banks accessible by a MAP engine of the plurality of MAP engines; and wherein when the turbo decoder is operating in HSDPA mode the plurality of extrinsic memory banks is configured such that during a first half of a decoding iteration, the MAP engine is able to read a first dataset from and write second dataset to the plurality of extrinsic memory banks in natural row and column order, and during a second half of the decoding iteration, the MAP engine is able to read a third dataset from and write a fourth dataset to the plurality of extrinsic memory banks in a predetermined row and column order in accordance with an interleaver table using a read column buffer and a write column buffer.
Tracking Method And Device Adopting A Series Of Observation Models With Different Life Spans
Haizhou Ai - Beijing, CN Yuan Li - Los Angeles CA, US Shihong Lao - Kyoto, JP Takayoshi Yamashita - Kizugawa, JP
Assignee:
Omron Corporation - Kyoto Tsinghua University - Beijing
International Classification:
G06K 9/00
US Classification:
382103, 382165
Abstract:
The present invention relates to a tracking method and a tracking device adopting multiple observation models with different life spans. The tracking method is suitable for tracking an object in a low frame rate video or with abrupt motion, and uses three observation models with different life spans to track and detect a specific subject in frame images of a video sequence. An observation model I performs online learning with one frame image prior to the current image, an observation model II performs online learning with five frames prior to the current image, and an observation model III is offline trained. The three observation models are combined by a cascade particle filter so that the specific subject in the low frame rate video or the object with abrupt motion can be tracked quickly and accurately.
Yuan Li - Los Angeles CA, US Hartwig Adam - Marina del Rey CA, US
Assignee:
Google Inc. - Mountain View CA
International Classification:
G06K 9/62
US Classification:
382159, 382157, 382160, 382161, 382209
Abstract:
Systems and methods for improving visual object recognition by analyzing query images are disclosed. In one example, a visual object recognition module may determine query images matching objects of a training corpus utilized by the module. Matched query images may be added to the training corpus as training images of a matched object to expand the recognition of the object by the module. In another example, relevant candidate image corpora from a pool of image data may be automatically selected by matching the candidate image corpora against user query images. Selected image corpora may be added to a training corpus to improve recognition coverage. In yet another example, objects unknown to a visual object recognition module may be discovered by clustering query images. Clusters of similar query images may be annotated and added into a training corpus to improve recognition coverage.
Systems And Methods For Matching Visual Object Components
Yuan Li - Los Angeles CA, US Hartwig Adam - Marina del Rey CA, US
Assignee:
Google Inc. - Mountain View CA
International Classification:
G06K 9/62
US Classification:
382159, 382209
Abstract:
Systems and methods for modeling the occurrence of common image components (e. g. , sub-regions) in order to improve visual object recognition are disclosed. In one example, a query image may be matched to a training image of an object. A matched region within the training image to which the query image matches may be determined and a determination may be made whether the matched region is located within an annotated image component of the training image. When the matched region matches only to the image component, an annotation associated with the component may be identified. In another example, sub-regions within a plurality of training image corpora may be annotated as common image components including associated information (e. g. , metadata). Matching sub-regions appearing in many training images of objects may be down-weighted in the matching process to reduce possible false matches to query images including common image components.
Methods And Apparatus To Perform Closed-Loop Transmit Diversity With Frequency-Domain Equalizers
Yuan Li - San Diego CA, US Toshio Nagata - San Diego CA, US Raied Salem - Spring Valley CA, US
International Classification:
H04B 1/00 H04L 27/28
US Classification:
375147000, 375260000
Abstract:
Methods and apparatus to perform closed-loop transmit diversity with frequency-domain equalizers in high-speed downlink packet access (HSDPA) receivers are disclosed. An example method comprises receiving a first signal representative of a first code division multiple access (CDMA) signal received from a first transmit antenna and a second signal representative of a second CDMA signal received from a second transmit antenna, computing a first channel estimate for a first path from the first transmit antenna to the receiver, computing a second channel estimate for a second path from the second transmit antenna to the receiver, and computing a frequency-domain equalizer (FDE) coefficient for the first path based on the first and the second channel estimates.
Methods And Apparatus To Perform Fractional-Spaced Channel Estimation For Frequency-Domain Equalizers
Toshio Nagata - San Diego CA, US Yuan Li - San Diego CA, US Raied Salem - Spring Valley CA, US
International Classification:
H04B 1/00 H04K 1/10
US Classification:
375147000, 375260000
Abstract:
Methods and apparatus to perform fractional-spaced channel estimation for frequency-domain equalizers in high-speed downlink packet access (HSDPA) receivers are disclosed. An example method comprises computing a first fractionally-spaced time-domain channel estimate from an oversampled CDMA signal, and computing a first chip-interval frequency-domain equalizer (FDE) coefficient from the first fractionally-spaced channel estimate.
Dr. Li graduated from the Sun Yat Sen Univ of Med Sci, Guangzhou, China (242 21 Pr 1/71) in 1987. She works in Flushing, NY and specializes in Internal Medicine. Dr. Li is affiliated with Flushing Hospital Medical Center and Queens Hospital Center.
Name / Title
Company / Classification
Phones & Addresses
Yuan Li
U.S. Investment Regional Center, LLC
801 E Walnut St, Pasadena, CA 91101
Yuan Zheng Li
GOLDEN FLOWER INC
Yuan Li
CROSS TIME INTERNATIONAL TRADE LLC
Yuan W Li
JING & YINGS FOOD INC
Yuan Li President
SUNRISE CAREGIVER FOUNDATION INC Civic/Social Association
5670 Wilshire Blvd STE 1410, Los Angeles, CA 90036 388 E Vly Blvd, Alhambra, CA 91801
Yuan Ming Li President
Jetta Tours & Bus Corporation
12711 Ramona Blvd, Duarte, CA 91706
Yuan Yuan Li President
GALAXY TECHNOLOGY (US) LTD
6170 Stonebridge Ave, Westminster, CA 92683
Yuan Li President
TENGHUA INTERNATIONAL TRADE CO
401 S Los Angeles St STE 7, Los Angeles, CA 90013
Googleplus
Yuan Li
Work:
Atkins - Assistant Engineer
Education:
University of Bristol - MSc IASD, University of Bristol - BSc Engineering Design
Yuan Li
Education:
Georgetown University - Communication, Culture and Technology, Peking University - Journalism
Yuan Li
About:
嗯!我是蒝
Yuan Li
Education:
Peking unie medical college
Yuan Li
Education:
Laoheshan Vocational School of Technology/老和山職業技術學院