Tiffany & Co.
Lead Engineer - Unified Communications and Contact Centers
Bt Jan 2008 - Aug 2016
Enterprise Solutions Architect
At&T Jan 2007 - Dec 2007
Senior Networking Consultant
Finisar Corporation (Nasdaq: Fnsr) Jan 2004 - Dec 2006
Principal Engineer and Project Manager
Jedai Broadband Networks Jul 2000 - Dec 2003
Principal Engineer
Education:
Virginia Tech
Masters, Electronics Engineering
Skills:
Cisco Ccie Collaboration Ieee Senior Member 2 Us Patents 21 Peer Reviewed Publications
Languages:
English Tamil Hindi
Certifications:
License 51214 Ccnp (R&S) Ccie Collaboration
Us Patents
Tandem Optoelectronic Transciver Package And Method Of Operating An Optical Fiber Communication Network Employing The Same
Robert Buss - Brick NJ, US John Loughlin - Lebanon NJ, US Emory Anderson - Forest Hills NY, US Anthony Jayakumar - Bridgewater NJ, US Michael Guarnaccia - Allendale NJ, US
International Classification:
H04B010/00
US Classification:
359/152000, 359/163000
Abstract:
An optical transceiver circuit pack in which specialized components, i.e., optical components associated with transmitting and receiving at a first wavelength or first band of wavelengths, are arranged on a first optical transceiver card section constituting a first module, and wherein generic components, i.e., electronic components which are arranged and operable to electrically interact with any first module regardless of its particular wavelength or band of wavelengths, are arranged on a second optical transceiver card section constituting a second module, the respective modules being detachably coupled to one another such that the first module may be replaced with either an identical module (i.e., one being configured to transmit and receive at said first wavelength or first band of wavelengths) or a different module (i.e., one being configured to transmit at a wavelength or band of wavelengths different than said first wavelength or first band of wavelengths. Advantageously, it is no longer necessary to maintain, in an inventory of spares, an entire optical transceiver circuit pack for each different operating wavelength of an optical communication system. Rather, a comparatively small number of second modules may be stored relative to the number of first modules since the former are common to all of the transceiver circuit packs regardless of transmission wavelength. As such, the overall cost of maintaining an adequate inventory of spare optical transceiver circuit packs is substantially reduced.
Low Cost, All Electronic And Unobtrusive Method Of Implementing A Wavelength Supervisory Channel For The Control And Management Of Individual And Multiple Wavelengths In An Optical Communication System
The wavelength supervisory channel is a mechanism for transmitting and receiving control and management information about the wavelength in a multi-wavelength communication system. A plurality of these channels, each being carried on their respective wavelengths can enable a redundant, robust and fault tolerant method of transmitting and receiving the aforementioned control information for the entire communications network comprised of many such optical devices replacing the traditional and more expensive optical supervisory channel or digital wrapper techniques. The invention described below details one embodiment of the wavelength supervisory channel implemented as a sub-carrier modulated orthogonal channel, riding along with the main payload data channel, in an all-electronic, low cost and unobtrusive methodology.
Adaptive Equalizer Using Self-Learning Neural Network
Joshua Alspector - Westfield NJ Timothy X. Brown - Mendham NJ Anthony Jayakumar - Somerset NJ
Assignee:
Bell Communications Research Inc. - Livingston NJ
International Classification:
H03H 730
US Classification:
375230
Abstract:
A channel equalizer is formed using a self-learning neural network. During a training period, the neural network is taught the channel response function. The network is then used to equalize distortions introduced into signals by the channel. The neural network may be a Boltzmann Machine type of neural network comprising neurons arranged in an input layer, a hidden layer, and an output layer. The neurons are interconnected by bidirectional symmetric weighted synapses. Each neuron is preferably implemented by an analog integrated circuit. Direct communication between the input and output layers helps in faster channel acquisition. The scheme can very easily be extended to multilevel and multisymbol modulation schemes such as QAM and PSK.
Joshua Alspector - Westfield NJ Anthony Jayakumar - Somerset NJ
Assignee:
Bell Communications Research, Inc. - Livingston NJ
International Classification:
H03K 1908 H03K 192
US Classification:
395 24
Abstract:
A neuron for use in a self-learning neural network comprises a current input node at which a plurality of synaptic input currents are summed using Kirchoff's current law. The summed input currents are normalized using a coarse gain current normalizer. The normalized summed inputs current is then converted to a voltage using a current to voltage converter. This voltage is then amplified by a gain controlled cascode output amplifier. Gain control inputs are provided in the output amplifier so that the neuron can be settled by the Mean Field Approximation. A noise input stage is also connected to the output amplifier so that the neuron can be settled using simulated annealing. The resulting neuron is a variable gain, bi-directional current transimpedance neuron with a controllable noise input.
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