Mitsubishi Electric Research Laboratories, Inc.

Disney Enterprises, Inc.

Mitsubishi Electric Research Labs.

Mitsubishi Electric Corporation

Jonathan S Yedidia

Yige Wang

Anthony Vetro

Stark Draper

Emin Martinian

Andreas F Molisch

Nate Derbinsky

William T Freeman

Neelesh B Mehta

Stark C Draper

Charles Mathy

Jose Bento Ayres Pereira

Marc P C Fossorier

Philip Orlik

Jinyun Zhang

Shantanu Rane

Zafer Sahinoglu

Zhifeng Tao

Ali Azarbayejani

Ying-zong Huang

Juntan Zhang

Ashish Khisti

Jean-Philippe M Bouchaud

Jose Bento

Dan Schmidt

Veit Elser

Yagiz Sutcu

Sergey M Yekhanin

Jin Zhang

Karunakar Pedagani

Jinghu Chen

Ravi Palanki

Yair Weiss

A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables where the cost functions have a relationship with the variables and receiving a landmark indicating a point that an agent is to visit while moving, a cost being associated with ignoring the landmark. The method includes generating a first message for the cost functions for the corresponding variable based upon the relationship and a second message for each of the variables for the corresponding cost function based upon the relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes repeating steps (c), (d), and (e) until a consensus is formed between the first and second messages until the optimization solution is determined based upon the consensus.

Method and device for multi-agent path planning

A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables in which each of the cost functions has a predetermined relationship with select ones of the variables. The variables comprise a sub-solution of a spline indicative of a curved path along an estimated trajectory. The method includes generating a first message for each of the cost functions for each corresponding variable based upon the relationship and a second message for each of the variables for each corresponding cost function based upon the relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes forming a consensus between the first and second messages until the optimization solution is determined.

Method and device for three-weight message-passing optimization scheme using splines

A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables in which each of the cost functions has a predetermined relationship with select ones of the variables. The method includes generating a first message for each of the cost functions for each corresponding variable based upon the respective predetermined relationship and a second message for each of the variables for each corresponding cost function based upon the respective predetermined relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes repeating steps (b), (c), and (d) until a consensus is formed between the first and second messages until the optimization solution is determined based upon the consensus.

Method and device for three-weight message-passing optimization scheme

There is provided a system and method for training and utilizing a boundary graph machine learning algorithm. The system including a processor configured to receive a plurality of entry nodes, each of the plurality of entry nodes including an entry node input and an entry node output, add each of the plurality of entry nodes to a graph using the entry node input and the entry node output, receiving a plurality of training nodes, each of the plurality of training nodes including a training node input and a training node output, add each of the plurality of training nodes to the graph when the training node input for each of the plurality of training nodes is similar to the training node output of a closest node and the training node output of each of the plurality of training nodes is different than the training node output of the closest node.

Boundary graph machine learning algorithm for regression and classification

A system and a method for determining a quasi-cyclic (QC) low-density parity-check (LDPC) code, such that the QC LDPC code has no trapping sets are disclosed. A set of matrices representing a family of QC LDPC codes are acquired, wherein each QC LDPC code is a tail-biting spatially-coupled code of girth not less than eight, and wherein each column of each matrix in the set has a weight not less than four. Based on a trapping set pattern, a matrix from the set of matrices is selected such that the matrix represents the QC LDPC code with no trapping sets. The matrix can be stored into a memory.

Quasi-cyclic low-density parity-check codes

A method estimates parameters of 3-phase voltage signals to synchronize a power grid in a presence of a voltage unbalance by transforming the 3-phase voltage signals to &#x3b1;&#x3b2;-reference signals using a Clarke transformation matrix, and estimating sinusoidal signals and corresponding quadrature signals of the &#x3b1;&#x3b2;-reference signals using an extended Kalman filter, and determining a phase angle of a positive sequence based on a relationship of the phase angle to the estimated the sinusoidal signals.

System and method for determining quasi-cyclic low-density parity-check codes having high girth

A method and system manage a hierarchy of passwords for users accessing a hierarchy of access control devices. First, a codeword is acquired and a syndrome of the codeword is determined. Next, the codeword is randomly modified with a probability p to produce a modified codeword. The modified codeword is selected and assigned to a user as a password, if the modified codeword is recoverable.

Method and system for managing a hierarchy of passwords

A code to be decoded by message-passing is represented by a factor graph. The factor graph includes variable nodes indexed by i and constraint nodes indexed by a connected by edges for transferring messages moutgoing from the variable nodes to the constraint nodes and messages mincoming from the constraint nodes to the variable nodes. The messages mare initialized based on beliefs bof a received codeword. The messages mare generated by overshooting the messages mat the constraint nodes. The beliefs bare updated at the variable nodes using the messages m. The codeword is outputted if found, otherwise, the messages mare updated using a correction for the overshooting.

Method and system for decoding graph-based codes using message-passing with difference-map dynamics

Biometric parameters acquired from human faces, voices, fingerprints, and irises are used for user authentication and access control. Because the biometric parameters are continuous and vary from one reading to the next, syndrome codes are applied to determine biometric syndrome vectors. The biometric syndrome vectors can be stored securely, while tolerating an inherent variability of biometric data. The stored biometric syndrome vector is decoded during user authentication using biometric parameters acquired at that time. The syndrome codes can also be used to encrypt and decrypt data. The biometric parameters can be pre-processed to form a binary representation, in which the binary representation has a set of predetermined statistical properties enforced imposed by a set of binary logical conditions.

Pre-processing biometric parameters before encoding and decoding

A multi-stage decoder decodes a block of symbols, received via a noisy channel, to a codeword. The decoder includes multiple sub-decoders connected sequentially, and wherein a next sub-decoder has a slower processing time and better word error rate than a previous sub-decoder, and wherein the next sub-decoder is only executed if the previous decoder fails to decode the block sequence of symbols, and a last sub-decoder is executed until a termination condition is reached.

Multi-stage decoder for error-correcting codes

A method constructs a code, wherein the code is a large-girth quasi-cyclic low-density parity-check code. A base matrix is selected for the code. A cost matrix corresponding to the base matrix is determined. A single element in the base is changed repeatedly maximize a reduction in cost. A parity check matrix is constructing for the code from the base matrix when the cost is zero, and an information block is encoded as a code word using the parity check matrix in an encoder.

Method for constructing large-girth quasi-cyclic low-density parity-check codes

A method and system decode a sequence of symbols received via a channel to a codeword of an error-correcting code. Log-likelihood ratios are determined from a sequence of symbols received via a channel. A set of constraints is initialized according to the log-likelihood ratios. An adaptive linear programming decoder is applied to the set of constraints and the log- likelihood ratios according to an error-correcting code to produce an estimate of the codeword and an updated set of constraints. If the estimate of the codeword is a non-integer pseudo codeword, further update the set of updated constraints with a set of integer constraints if the estimate of the codeword is the non-integer pseudo codeword, and proceeding with the applying step, and otherwise producing the estimate of the codeword as the final codeword.

Maximum likelihood decoding via mixed-integer adaptive linear programming

A method represents a correlated set of images. The correlation can be spatial or temporal. A lossy operation is applied to each image in the correlated set to generate a coarse image. The coarse image is encoded losslessly to yield an encoded coarse image. Each image is also represented by syndrome bits. The combination of the encoded coarse images and the syndrome bits represent the correlated set of images.

Coding correlated images using syndrome bits

Biometric parameters acquired from human forces, voices, fingerprints, and irises are used for user authentication and access control. Because the biometric parameters are continuous and vary from one reading to the next, syndrome codes are applied to determine biometric syndrome vectors. The biometric syndrome vectors can be stored securely while tolerating an inherent variability of biometric data. The stored biometric syndrome vector is decoded during user authentication using biometric parameters acquired at that time. The syndrome codes can also be used to encrypt and decrypt data.

Biometric based user authentication and data encryption

A system and method for communicating information in a wireless cooperative relay network of nodes, the nodes including a source, a set of relays, and a destination. The source broadcasts a code word encoded as a data stream using a rateless code. The relays receive the data stream, decode the data stream to recover the code word, and reencode and transmit the recovered code word as the data stream with the rateless code. The destination receives and decodes the reencoded data streams to recover the code word.

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Burbank, CA, United States of America

Jonathan S Yedidia