Abstract:
A computer-aided design method for developing, simulating, and testing a read-channel architecture to be implemented in a VLSI circuit. The method uses a coset operating mode and nonzero-syndrome-based decoding to accelerate the simulation of the read-channel's error-rate characteristics corresponding to different parity-check matrices employed in the read-channel's turbo-decoder, such as a low-density parity-check decoder. The acceleration is achieved through recycling some previously generated log-likelihood-ratio values, which enables the method to sometimes bypass certain time-consuming processing steps therein.
Abstract:
A method and system for key frame based region of interest (ROI) tracking is disclosed. The method includes storing a key ROI set in a key ROI buffer, the key ROI set including at least one key ROI; designating one of the key ROI in the key ROI set as an active key ROI; receiving a point cloud representing a particular ROI to be processed for tracking; establishing a correspondence between that particular ROI and the active key ROI; determining whether to switch the active key designation to another key ROI in the key ROI set and switching the active key designation accordingly; and determining whether to modify the key ROI set and modifying the key ROI set accordingly.
Abstract:
A method for estimating error rates in low-density parity check codes includes calibrating an encoder according to specific channel parameters and according to dominant error events in the low-density parity-check code. Dominant codewords are classified based on characteristics of each codeword that are likely to produce similar error rates at similar noise levels; codeword classes that produce the highest error rate are then tested. Error boundary distance is estimated using multiple binary searches on segments. Segments are defined based on codeword, trapping set and biasing noise components of the channel. To improve calculation speed the most significant subclasses of codewords, trapping sets and noise signals are used.
Abstract:
A method for estimating error probability of LDPC codes includes ordering LDPC codes according to features in each code with known error characteristics. The method includes identifying features in each LDPC code having known error characteristics; adding each code to one or more categories based on the existence of such features; and ranking the LDPC codes according to the level of error risk.
Abstract:
A method and system for key frame based region of interest (ROI) tracking is disclosed. The method includes storing a key ROI set in a key ROI buffer, the key ROI set including at least one key ROI; designating one of the key ROI in the key ROI set as an active key ROI; receiving a point cloud representing a particular ROI to be processed for tracking; establishing a correspondence between that particular ROI and the active key ROI; determining whether to switch the active key designation to another key ROI in the key ROI set and switching the active key designation accordingly; and determining whether to modify the key ROI set and modifying the key ROI set accordingly.
Abstract:
Superresolution image processing that can be applied when two image frames of the same scene are available so that image information from one frame can be used to enhance the image from the other frame. The superresolution image processing uses a sparse matrix generated based on a Markov random field defined over these two image frames. The sparse matrix is inverted and applied to the image data from the image frame that is being enhanced to generate a corresponding enhanced image.
Abstract:
A method for estimating error rates in low-density parity check codes includes calibrating an encoder according to specific channel parameters and according to dominant error events in the low-density parity-check code. Dominant codewords are classified based on characteristics of each codeword that are likely to produce similar error rates at similar noise levels; codeword classes that produce the highest error rate are then tested. Error boundary distance is estimated using multiple binary searches on segments. Segments are defined based on codeword, trapping set and biasing noise components of the channel. To improve calculation speed the most significant subclasses of codewords, trapping sets and noise signals are used.
Abstract:
A machine-implemented method of generating trapping-set information for use in LDPC-decoding processing of read signals generated, e.g., by sensing a storage medium, such as a magnetic platter. In one embodiment, the method can be implemented as an add-on to any other trapping-set search method in which the discovered trapping sets are evaluated to determine their influence on the overall bit-error rate and/or error-floor characteristics of the LDPC decoder. The method can advantageously reuse at least some of the computational results obtained during this evaluation, thereby requiring a relatively small amount of additional computations, while providing a significant benefit of discovering many more trapping sets in addition to the ones that are being evaluated.
Abstract:
In one embodiment, a programmable vector processor performs preamble detection in a wireless communication network. Implementation of preamble detection in the vector processor is made possible by a set of vector instructions that include (i) a circular load instruction for loading vectors of received data, (ii) a correlation instruction for correlating the vectors of received data with vectors of the scrambling code to concurrently generate a plurality of complex correlations, (iii) a partial-transpose instruction for arranging vectors of the complex correlations for use by a Fast Hadamard Transform (FHT) processor, and (iv) an FHT instruction for performing FHT processing on a vector of complex correlations. Implementing preamble detection in the vector processor allows more of the received data to be processed concurrently. As a result, preamble detectors of the disclosure may detect preambles using fewer clock cycles than that of comparable preamble detectors implemented using hardware accelerators.
Abstract:
A method for estimating error probability of LDPC codes includes ordering LDPC codes according to features in each code with known error characteristics. The method includes identifying features in each LDPC code having known error characteristics; adding each code to one or more categories based on the existence of such features; and ranking the LDPC codes according to the level of error risk.