1170 results about "Basis function" patented technology

A signal processor generates basis functions and identifies at least one basis function component of a sensor signal in order to calculate a physiological measurement. The signal processor is advantageously applied to pulse oximetry so as to directly calculate oxygen saturation and so as to calculate a robust oxygen saturation measurement. In particular, a signal component transform may be calculated within a window around a derived pulse rate estimate. A signal component transform may also utilize sinusoidal basis functions, and an optimization of a signal component transform may occur at a particular frequency or a set of frequencies. A sinusoidal waveform or waveforms at that frequency or set of frequencies is generated to select associated red and infrared components of the sensor signal, and an oxygen saturation is calculated from a magnitude ratio of these components.

Described is an active learning system for fingerprinting an object identified in an image frame. The active learning system comprises a flow-based object segmentation module for segmenting a potential object candidate from a video sequence, a fixed-basis function decomposition module using Haar wavelets to extract a relevant feature set from the potential object candidate, a static classifier for initial classification of the potential object candidate, an incremental learning module for predicting a general class of the potential object candidate, an oriented localized filter module to extract features from the potential object candidate, and a learning-feature graph-fingerprinting module configured to receive the features and build a fingerprint of the object for tracking the object.

A method of building predictive statistical models provides a dedicated aggregation module for each transactional record source. Each aggregation module aggregates the transactional records using a neural network function to produce a scalar output which can then be input to a traditional modeling function, which may employ either logistic regression, neural network, or radial basis function techniques. The output of the aggregation modules can be saved, and updated aggregation values can be updated by processing new transaction records and combining the new transaction values with the previous output values using a blending function. Parameters of the neural network in the aggregation module may be calculated simultaneously with the parameters of the traditional modeling module.

Adaptive controller apparatus of a plant may be implemented. The controller may comprise an encoder block and a control block. The encoder may utilize basis function kernel expansion technique to encode an arbitrary combination of inputs into spike output. The controller may comprise spiking neuron network operable according to reinforcement learning process. The network may receive the encoder output via a plurality of plastic connections. The process may be configured to adaptively modify connection weights in order to maximize process performance, associated with a target outcome. The relevant features of the input may be identified and used for enabling the controlled plant to achieve the target outcome.

A multispectral X-ray imaging system uses a wideband source and filtration assembly to select for M sets of spectral data. Spectral characteristics may be dynamically adjusted in synchrony with scan excursions where an X-ray source, detector array, or body may be moved relative to one another in acquiring T sets of measurement data. The system may be used in projection imaging and/or CT imaging. Processed image data, such as a CT reconstructed image, may be decomposed onto basis functions for analytical processing of multispectral image data to facilitate computer assisted diagnostics. The system may perform this diagnostic function in medical applications and/or security applications.

A digital communications transmitter (100) includes a digital linear-and-nonlinear predistortion section (200, 1800, 2800) to compensate for linear and nonlinear distortion introduced by transmitter-analog components (120). A direct-digital-downconversion section (300) generates a complex digital return-data stream (254) from the analog components (120) without introducing quadrature imbalance. A relatively low resolution exhibited by the return-data stream (254) is effectively increased through arithmetic processing. Distortion introduced by an analog-to-digital converter (304) may be compensated using a variety of adaptive techniques. Linear distortion is compensated using adaptive techniques with an equalizer (246) positioned in the forward-data stream (112). Nonlinear distortion is then compensated using adaptive techniques with a plurality of equalizers (226) that filter a plurality of orthogonal, higher-ordered-basis functions (214) generated from the forward-data stream (112). The filtered-basis functions are combined together and subtracted from the forward-data stream (112).

The invention discloses a method for recognizing a road traffic sign for an unmanned vehicle, comprising the following steps of: (1) changing the RGB (Red, Green and Blue) pixel value of an image to strengthen a traffic sign feature color region, and cutting the image by using a threshold; (2) carrying out edge detection and connection on a gray level image to reconstruct an interested region; (3) extracting a labeled graph of the interested region as a shape feature of the interested region, classifying the shape of the region by using a nearest neighbor classification method, and removing a non-traffic sign region; and (4) graying and normalizing the image of the interested region of the traffic sign, carrying out dual-tree complex wavelet transform on the image to form a feature vector of the image, reducing the dimension of the feature vector by using a two-dimension independent component analysis method, and sending the feature vector into a support vector machine of a radial basis function to judge the type of the traffic sign of the interested region. By using the method, various types of traffic signs in a running environment of the unmanned vehicle can be stably and efficiently detected and recognized.

A system and method of intelligent navigation with collision avoidance for a vehicle is provided. The system includes a global positioning system and a vehicle navigation means in communication with the global positioning system. The system also includes a centrally located processor in communication with the navigation means, and an information database associated with the controller, for identifying a location of a first vehicle and a second vehicle. The system further includes an alert means for transmitting an alert message to the vehicle operator regarding a collision with a second vehicle. The method includes the steps of determining a geographic location of a first vehicle and a second vehicle within an environment using the global positioning system on the first vehicle and the global positioning system on the second vehicle, and modeling a collision avoidance domain of the environment of the first vehicle as a discrete state space Markov Decision Process. The methodology scales down the model of the collision avoidance domain, and determines an optimal value function and control policy that solves the scaled down collision avoidance domain. The methodology extracts a basis function from the optimal value function, scales up the extracted basis function to represent the unscaled domain, and determines an approximate solution to the control policy by solving the rescaled domain using the scaled up basis function. The methodology further uses the solution to determine if the second vehicle may collide with the first vehicle and transmits a message to the user notification device.

The invention discloses a face mage super-resolution method which fuses global features and local detail information. The invention can synthesize a high-resolution face image according to a low-resolution face image based on a sample image. Firstly, a local maintaining mapping algorithm and a radial basic function return algorithm are combined together to get a global high-resolution face image; then a neighborhood reconstruction method is adopted to synthesize a high-resolution face residual image block and consequently form a high-resolution face residual image by combination; finally, the high-resolution face residual image is overlapped to the high-resolution face image to obtain a final super-resolution effect. The technology provided by the invention can synthesize the clearer high-resolution face image, improve the recognition of the face image and have important application significances on video monitoring, face recognition and other aspects.

An RF transmitter (10) includes a nonlinear predistorter (24). The nonlinear predistorter (24) is implemented using adaptive equalizers (30′, 30″). A feedback signal (20) is developed by downconverting an RF communication signal (16). The feedback signal (20) is used in driving tap coefficients (34) for the adaptive equalizers (30′, 30″). The adaptive equalizers (30′, 30″) filter higher-ordered basis function signals (47′, 47″) generated from an excursion signal 13. The excursion signal 13 exhibits the same phase as a baseline communication signal (12) but has a magnitude that is reduced by a nonlinear threshold (100) when the baseline communication signal (12) exceeds the nonlinear threshold (100) and has a magnitude of zero at other times. The tap coefficients (34) may be formed from proto-coefficients (168) in response to the magnitude of the corresponding portion of the signal being filtered in the adaptive equalizers (30′, 30″).

Techniques for determining and using a thermodynamic model that characterizes a thermodynamic response of an enclosure conditioned by an HVAC system are disclosed. To determine a thermodynamic model, temperature information when the HVAC system operates in a first state may first be received. A response interval may then be determined where the response interval indicates an estimated time between when the HVAC system begins operating in the first state and when the temperature within the enclosure begins to change in a direction associated with the first state. Weighting factors corresponding to basis functions may then be determined, where the weighted basis functions characterize the temperature trajectory of the enclosure in response to the HVAC system operating in the first state. The basis functions may include a first basis function that is evaluated from a time that the HVAC system begins operating in the first state until a time when the response interval ends, and a second basis function that is evaluated beginning at the time when the response interval ends.

Adaptive controller apparatus of a plant may be implemented. The controller may comprise an encoder block and a control block. The encoder may utilize basis function kernel expansion technique to encode an arbitrary combination of inputs into spike output. The controller may comprise spiking neuron network operable according to reinforcement learning process. The network may receive the encoder output via a plurality of plastic connections. The process may be configured to adaptively modify connection weights in order to maximize process performance, associated with a target outcome. The relevant features of the input may be identified and used for enabling the controlled plant to achieve the target outcome. The stochasticity of the learning process may be modulated. Stochasticity may be increased during initial stage of learning in order to encourage exploration. During subsequent controller operation, stochasticity may be reduced to reduce energy use by the controller.

A digital communications transmitter (100) includes a digital linear-and-nonlinear predistortion section (200) to compensate for linear and nonlinear distortion introduced by transmitter-analog components (120). A direct-digital-downconversion section (300) generates a complex digital return-data stream (254) from the analog components (120) without introducing quadrature imbalance. A relatively low resolution exhibited by the return-data stream (254) is effectively increased through arithmetic processing. Linear distortion is first compensated using adaptive techniques with an equalizer (246) positioned in the forward-data stream (112). Nonlinear distortion is then compensated using adaptive techniques with a plurality of equalizers (226) that filter a plurality of orthogonal, higher-ordered-basis functions (214) generated from the forward-data stream (112). The filtered-basis functions are combined together and subtracted from the forward-data stream (112).

Systems and methods for transmitting data, including encoding one or more streams of input data using one or more adaptive Low Density Parity Check (LDPC) encoders, wherein the encoders generate one or more signal constellations; modulate one or more signals using hybrid multidimensional coded modulation; apply orthogonal prolate spheroidal wave functions as electrical basis functions; generate one or more spectral band group signals by selecting and combining two or more spectral band groups with center frequencies that are orthogonal to each other; and spectral-mode-multiplex and transmit the one or more adaptive LDPC-coded data streams including the one or more spectral band group signals combined into corresponding spatial modes over a transmission medium.

A digital communications transmitter (100) includes a digital linear-and-nonlinear predistortion section (200) to compensate for linear and nonlinear distortion introduced by transmitter-analog components (120). A direct-digital-downconversion section (300) generates a complex digital return-data stream (254) from the analog components (120) without introducing quadrature imbalance. A relatively low resolution exhibited by the return-data stream (254) is effectively increased through arithmetic processing. Linear distortion is first compensated using adaptive techniques with an equalizer (246) positioned in the forward-data stream (112). Nonlinear distortion is then compensated using adaptive techniques with a plurality of equalizers (226) that filter a plurality of orthogonal, higher-ordered-basis functions (214) generated from the forward-data stream (112). The filtered-basis functions are combined together and subtracted from the forward-data stream (112).

Entropy encoding is performed in the inventive apparatus and method in response to the scanning of transform coefficients following an initial scanning pattern selected on the basis of probability statistics of non-zero coefficients for each block position. These non-zero probability statistics are ranked for a given combination of coding characteristics within the current block to arrive at an initial scanning pattern. The same initial scanning pattern selection is performed in the decoder to allow the transform coefficients to be extracted in their proper order from encoded video data. The pattern selection is applicable to both intra prediction and inter prediction. Transform coefficients are more accurately ordered in response to the invention because in adapting pattern initialization to quantization step size, high-frequency basis functions are properly taken into account.

Embodiments disclosed herein provide methods and systems for delineating cell nuclei and classifying regions of histopathology or microanatomy while remaining invariant to batch effects. These systems and methods can include providing a plurality of reference images of histology sections. A first set of basis functions can then be determined from the reference images. Then, the histopathology or microanatomy of the histology sections can be classified by reference to the first set of basis functions, or reference to human engineered features. A second set of basis functions can then be calculated for delineating cell nuclei from the reference images and delineating the nuclear regions of the histology sections based on the second set of basis functions.

A trajectory is generated using non-uniform rational B-splines. A feasible corridor is approximated with at least one convex polytope. The at least one convex polytope is defined by a plurality of vertices. The feasible corridor comprises a region in a trajectory space that satisfies a plurality of trajectory constraints for a vehicle to pass through the trajectory space. The vehicle comprises a plurality of vehicle constraints. A non-uniform rational B-spline (NURBS) definition is constructed that comprises: a plurality of NURBS basis functions, a plurality of control points that comprise the plurality of vertices, and a plurality of weight points. The plurality of vehicle constraints are parameterized with the plurality of NURBS basis functions. At least one trajectory is generated for the vehicle through the trajectory space where the at least on trajectory lies within the feasible corridor to satisfy the plurality of trajectory constraints.

Apparatus, methods, and computer program products are disclosed that accumulate a presence history of an entity within a persistent virtual environment by repeated gathering of virtual presence information. The virtual presence information includes an entity identification value and a sampling time value. Once the virtual presence information is collected, the technology performs a general least-squares-fit to a set of basis functions on a portion of the presence history to create a coefficient vector. The coefficient vector represents a temporal profile consistent with the presence history and includes coefficients responsive to the general least-squares-fit. Once the coefficient vector is created, the technology characterizes the entity responsive to its coefficient vector and presents the characterization of the entity.