57results about How to "More computationally efficient" patented technology

This invention is a method for binaural localization using a cascade of resonators and anti-resonators to implement an HRTF (head-related transfer function). The spectrum of the cascade reproduces the magnitude spectrum of a desired HRTF. The proposed method provides a considerably more computationally efficient implementation of HRTF filters with no detectable deterioration of output quality while saving memory when storing a large quantity of HRTFs due to the parameterization of its resonators and anti-resonators. Finally, the method offers additional flexibility since the resonators and anti-resonators can be manipulated individually during the design process, making it possible to interpolate smoothly between HRTFs, reduce spectral coloring or achieve higher accuracy at perceptually relevant frequency regions. These HRTF are useful in stereo enhancement and multi-channel virtual surround simulation.

A graphics processing architecture employing a single shader is disclosed. The architecture includes a circuit operative to select one of a plurality of inputs in response to a control signal; and a shader, coupled to the arbiter, operative to process the selected one of the plurality of inputs, the shader including means for performing vertex operations and pixel operations, and wherein the shader performs one of the vertex operations or pixel operations based on the selected one of the plurality of inputs. The shader includes a register block which is used to store the plurality of selected inputs, a sequencer which maintains vertex manipulation and pixel manipulations instructions and a processor capable of executing both floating point arithmetic and logical operations on the selected inputs in response to the instructions maintained in the sequencer.

An event clustering method uses foreground and background segmentation for clustering images from a group into similar events. Initially, each image is divided into a plurality of blocks, thereby providing block-based images. Utilizing a block-by-block comparison, each block-based image is segmented into a plurality of regions comprising at least a foreground and a background. One or more luminosity, color, position or size features are extracted from the regions and the extracted features are utilized to estimate and compare the similarity of the regions comprising the foreground and background in successive images in the group. Then, a measure of the total similarity between successive images is computed, thereby providing image distance between successive images, and event clusters are delimited from the image distances.

An Intelligent Tutoring System (ITS) system is provided that is able to identify and respond adaptively to the learner's or student's affective states (i.e., emotional states such as confusion. frustration, boredom, and flow/engagement) during a typical learning experience, in addition to adapting to the learner's cognitive states. The system comprises a new signal processing model and algorithm, as well as several non-intrusive sensing devices, and identifies and assesses affective states through dialog assessment techniques, video capture and analysis of the student's face, determination of the body posture of the student, pressure on a pressure sensitive mouse, and pressure on a pressure sensitive keyboard. By synthesizing the output from these measures, the system responds with appropriate conversational and pedagogical dialog that helps the learner regulate negative emotions in order to promote learning and engagement.

One embodiment described herein provides a system and method for establishing a secure communication channel between a client and a server. During operation, the client generates a service request comprising a first dynamic message, transmits the first service request to the server, which authenticates the client based on the first dynamic message, and receives a second dynamic message from the server in response to the first dynamic message. The client authenticates the server based on the second dynamic message, and negotiates, via a quantum-key-distribution process, a secret key shared between the client and the server. The client and server then establish a secure communication channel based on at least a first portion of the secret key.

Aspects relate to systems and methods for improving the operation of computer-implemented neural networks. Some aspects relate to training a neural network using a compressed representation of the inputs either through efficient discretization of the inputs, or choice of compression. This approach allows a multiscale approach where the input discretization is adaptively changed during the learning process, or the loss of the compression is changed during the training. Once a network has been trained, the approach allows for efficient predictions and classifications using compressed inputs. One approach can generate a larger more diverse training dataset based on both simulations from physical models, as well as incorporating domain expertise and other available information. One approach can automatically match the documents to the list, while still allowing a user to input information to update and correct the matching process.

This invention relates to alternative, synthesisable trend-following strategy, based on a rolling, delta-spliced lookback straddle. This operates like a conventional lookback straddle, except that the time to expiry, rather than monotonically running down to zero, is reset where possible to that of a ‘younger’ straddle, provided that the delta of the two straddles does not differ by more than a specified amount. It is more computationally efficient than prior art approaches; further, it does not lead to positions being prematurely liquidated.

Embodiments of the invention relate to computer-implemented methods and systems for managing and analyzing subscriber history data present within a service provider infrastructure. The subscriber history data is free of personally identifiable information and is aggregated according to an anonymous attribute. A predictive model is used to rank a plurality of individuals or households according to one or more household attributes, such as media habits and/or media exposure. Advertisers are provided with access to the ranked data, such that the advertisers can improve marketing metrics for advertisements delivered to the households. Service providers may receive monetary compensation for providing access to the ranked data.

Techniques for concatenating, interpolating and upsampling pose transforms represented as dual quaternions are described, including: (1) derivation of a complex-valued matrix form of dual quaternions and dual quaternion operations; (2) derivation of a transformation operator on position vectors which obviates an explicit conversion to a classical 4×4 spatial transformation matrix and keeps results in complex-valued matrix space; (3) design for a generic lookup table system for functions to supply logarithm and exponentiations of the dual quaternion in its native format with trigonometry lookup tables to avoid precision issues when denominators tend to zero; and (4) a mechanism for wrapping the complex-exponentiation together with a simple complex arithmetic unit for computing dual quaternion macro-operations in both native dual quaternion space and through simplifications of the equivalent complex-valued matrix to compute dual quaternion operations such as inverses, multiplications, logarithms and exponentials in order to chain the pose transformations encoded within.

Techniques for securing and authenticating asynchronous messages using a key manager are provided. A first component sending an asynchronous message to a second component may identify itself to a key manager by a private key and may receive an encrypted signing key from the key manager. The first component may then hash message content, encrypt the hashed message content using the signing key, and send the encrypted result along with the original message content to the receiving component via asynchronous messaging. The receiving component, which may obtain a symmetric signing key from the key manager or from local storage, may decrypt the received encrypted result using the symmetric signing key, and may hash the received original message content using the same hashing algorithm as the sending component; if the two results match, the receiving component may determine that the message is authentic and uncorrupted.

The present invention is directed to a system and method for applying second- and higher-order logic to analysis of event descriptive information, such as alarms, error messages, and fault signals.

Aspects relate to systems and methods for improving the operation of computer-implemented neural networks. Some aspects relate to training a neural network using a compressed representation of the inputs either through efficient discretization of the inputs, or choice of compression. This approach allows a multiscale approach where the input discretization is adaptively changed during the learning process, or the loss of the compression is changed during the training. Once a network has been trained, the approach allows for efficient predictions and classifications using compressed inputs. One approach can generate a larger more diverse training dataset based on both simulations from physical models, as well as incorporating domain expertise and other available information. One approach can automatically match the documents to the list, while still allowing a user to input information to update and correct the matching process.

Methods and apparatus of channel estimation using time-domain parameter extraction are disclosed. The wireless channel can be modeled by a multipath model with a limited number of parameters in the continuous time domain. In the discrete time domain, the multipath model leads to channel impulse responses that have a limited number of channel taps with non-negligible energy. Extracting the time-domain parameters and then reconstructing the channel yields channel estimates that have better accuracy. Time-domain parameter extraction also has lower computational complexity than existing methods.

A video compression process speeds the optimal choice of quantizers for compressing a data stream by setting up the optimization problem as a path-optimization problem in configuration space and finding the lowest cost path through the configuration space. The process begins with a starting node (or “state”) and propagates least-cost waves through the space until a path is completed to the end. The process may continue using uncompleted paths while their costs are less than the end state, beginning with the lowest cost incomplete path, until an improved path is found. The process may further continue, for a time constrained process, until time runs out or all useful possibilities are exhausted.

A fast conjugate phase reconstruction method for MRI is based on a polynomial expansion of the off-resonance phase accrual term. The expansion is truncated and can be a Taylor or Chebyshev expansion.

A system and method using inverse-vector processing to iterate through a loop of three steps: set a guide direction, invert opposite vectors, and average vectors to update the guide direction, for smoothing seismic amplitude data. The inverse-vector method can overcome instabilities where the traditional structure-tensor approach fails. The inverse-vector smoothing is simple to implement and more computational efficient. The resultant dips and azimuths are spatially consistent and thus more interpretable and suitable for calculation of curvature and other dip based attributes.