Oleg Sinyavskiy - San Diego CA, US Vadim Polonichko - San Diego CA, US
Assignee:
Brain Corporation - San Diego CA
International Classification:
G06N 3/08
US Classification:
706 25
Abstract:
Generalized learning rules may be implemented. A framework may be used to enable adaptive signal processing system to flexibly combine different learning rules (supervised, unsupervised, reinforcement learning) with different methods (online or batch learning). The generalized learning framework may employ average performance function as the learning measure thereby enabling modular architecture where learning tasks are separated from control tasks, so that changes in one of the modules do not necessitate changes within the other. Separation of learning tasks from the control tasks implementations may allow dynamic reconfiguration of the learning block in response to a task change or learning method change in real time. The generalized learning apparatus may be capable of implementing several learning rules concurrently based on the desired control application and without requiring users to explicitly identify the required learning rule composition for that application.
Apparatus And Methods For Efficient Updates In Spiking Neuron Network
Oleg Sinyavskiy - San Diego CA, US Vadim Polonichko - San Diego CA, US Eugene Izhikevich - San Diego CA, US
International Classification:
G06F 15/18
US Classification:
706 16
Abstract:
Efficient updates of connections in artificial neuron networks may be implemented. A framework may be used to describe the connections using a linear synaptic dynamic process, characterized by stable equilibrium. The state of neurons and synapses within the network may be updated, based on inputs and outputs to/from neurons. In some implementations, the updates may be implemented at regular time intervals. In one or more implementations, the updates may be implemented on-demand, based on the network activity (e.g., neuron output and/or input) so as to further reduce computational load associated with the synaptic updates. The connection updates may be decomposed into multiple event-dependent connection change components that may be used to describe connection plasticity change due to neuron input. Using event-dependent connection change components, connection updates may be executed on per neuron basis, as opposed to per-connection basis.
Method For Measuring River Discharge In The Presence Of Moving Bottom
Vadim Polonichko - San Diego CA, US Ramon Cabrera - Miami FL, US John Sloat - Las Vegas NV, US Matthew J. Hull - San Diego CA, US Arthur R. Schmidt - Tolono IL, US
Assignee:
YSI Incorporated - Yellow Springs OH
International Classification:
G01F 13/00
US Classification:
7317013, 7317003, 7317007, 7317029
Abstract:
A method for measuring channel flow discharge comprising the steps of: locating a platform carrying a fluid flow measurement device at a plurality of stations at spaced locations across a channel; determining the velocity of the platform at each station by averaging the differences between the position of the platform at a first time (t) and the position of the platform at a second time equal to the first time plus a position averaging interval (PI) for a plurality of different first times; obtaining current flow vs. depth profiles at each station by adjusting current velocity as measured by the current flow measuring device for the platform velocity; determining the flow discharge at each station.
Image Capture Device With An Automatic Image Capture Capability
- San Mateo CA, US Nicholas Ryan Gilmour - San Jose CA, US Vadim Polonichko - San Diego CA, US
International Classification:
H04N 5/232 H04N 1/21
Abstract:
An image capture device may automatically capture images. An image sensor may generate visual content based on light that becomes incident thereon. A depiction of interest within the visual content may be identified, and one or more images may be generated to include one or more portions of the visual content including the depiction of interest.
Systems And Methods For Spatially Selective Video Coding
A method for encoding images includes decoding a first encoded image to obtain a first decoded image, where the first decoded image includes a first decoded portion corresponding to a first encoded portion of the first encoded image and a second decoded portion corresponding to a second encoded portion of the first encoded image; decoding a second encoded image to obtain a second decoded image; combining the first decoded image and the second decoded image to obtain a single decoded image; and encoding the single decoded image to obtain a single encoded image that includes a third and a fourth encoded portions. Encoding the single decoded image includes obtaining the third encoded portion of the single encoded image by copying the first encoded portion of the first encoded image; and obtaining the fourth encoded portion of the single encoded image by encoding the second decoded portion using an encoder.
Image Capture Device With An Automatic Image Capture Capability
- San Mateo CA, US Nicholas Ryan Gilmour - San Jose CA, US Vadim Polonichko - San Diego CA, US
International Classification:
H04N 5/232 H04N 1/21
Abstract:
An image capture device may automatically capture images. An image sensor may generate visual content based on light that becomes incident thereon. A depiction of interest within the visual content may be identified, and one or more images may be generated to include one or more portions of the visual content including the depiction of interest.
- San Mateo CA, US David Newman - San Diego CA, US Vadim Polonichko - San Diego CA, US Tyler Gee - San Francisco CA, US Jessica Bonner - San Francisco CA, US
International Classification:
H04N 9/802 G11B 27/00 G11B 27/036
Abstract:
An image capture device may capture visual content during a visual capture duration and audio content during an audio capture duration. The audio capture duration may be shorter than the visual capture duration. The captured audio content may provide audio for playback of the captured visual content.
Generating Long Exposure Images For High Dynamic Range Processing
- San Mateo CA, US Vadim Polonichko - San Diego CA, US
International Classification:
H04N 5/235 H04N 5/225 H04N 5/232
Abstract:
Systems and methods are disclosed for generating long exposure images for high dynamic range processing. For example, methods may include receiving a short exposure image that was captured using an image sensor; receiving an additional image that was captured using the image sensor; determining a long exposure image based on the short exposure image and the additional image; applying high dynamic range processing to the short exposure image and the long exposure image to obtain an output image with a larger dynamic range than the short exposure image; and transmitting, storing, or displaying an image based on the output image.
Gazdzinski and Associates since 2009
Registered Patent Agent
Teledyne Technologies 2008 - 2009
Sr Systems Engineer
Assure Controls 2008 - 2008
Engineering Programs Manager
SonTek/YSI, Inc 2006 - 2007
Technical Fellow
SonTek/YSI, Inc 2001 - 2006
R&D Lead (Principal Engineer)
Education:
University of Victoria 1992 - 1998
Ph.D., Ocean Acoustics (Earth Sciences)
Moscow Institute of Physics and Technology 1982 - 1988
MS, Automation and Electronics
Skills:
Sensors Product Development Signal Processing Intellectual Property Algorithms Embedded Systems R&D Programming Patent Preparation Matlab Patent Prosecution Patent Portfolio Analysis Patent Drafting C Image Processing Patent Applications Patent Searching Data Analysis C++ Analysis Gps Navigation Mems Modeling Dsp
Languages:
Russian
Certifications:
Uspto Bar Salesforce Certified Administrator License 62,769 Uspto, License 62,769
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