Abstract: Embodiments of decoders supporting multiple code rates and code lengths for data storage systems are disclosed. The decoders can provide for flexible and scalable decoding, particularly when quasi-cyclic low-density parity-check code (QC-LDPC) decoding is used. The decoder can be scaled in size based on, for example, the desired decoding throughput and/or computational cycle duration. In one embodiment, a rotate-left/right shifter is configured to support data having processing units of one of multiple matrix sizes and independently shift portions of the data. In another embodiment, one or more decoding modules are configured to share with one or more other decoding modules an output value from a layer decoding operation. This sharing can facilitate parallel decoding of data by the decoding modules. As a result, decoding speed, efficiency, and system performance can be improved.

Abstract: An error management system for a data storage device can generate soft-decision log-likelihood ratios (LLRs) using multiple reads of memory locations. 0-to-1 and 1-to-0 bit flip count data provided by multiple reads of reference memory locations can be used to generate probability data that is used to generate possible LLR values for decoding target pages. Possible LLR values are stored in one or more look-up tables.

Abstract: Embodiments of decoders having early decoding termination detection are disclosed. The decoders can provide for flexible and scalable decoding and early termination detection, particularly when quasi-cyclic low-density parity-check code (QC-LDPC) decoding is used. In one embodiment, a controller iteratively decodes a data unit using a coding matrix comprising a plurality of layers. The controller terminates decoding the data unit in response to determining that the decoded data units from more than one layer decoding operation satisfy a parity check equation and that the decoded data units from more than one layer decoding operation are the same. Advantageously, the termination of decoding of the data unit can reduce a number of iterations performed to decode the data unit.

Abstract: The invention relates to the technical field of an alignment method, and discloses a method for aligning substrate and mask, including: firstly forming at least one set of alignment marks on a mask plate; selecting a certain number of large-size substrates as sample substrates; forming a plurality of sets of alignment marks on each sample substrate using the mask plate and the at least one set of alignment marks formed thereon to divide the sample substrate into a plurality of sub-substrate areas; and then performing mask process on the respective sample substrates, accurate alignment for each sub-substrate area can be realized by means of the plurality of sets of alignment marks on the sample substrate, and one sub-substrate area can be accurately aligned by means of at least two sets of alignment marks formed on the sample substrate.

Abstract: Aspects of the subject technology relate to a data storage system controller including a host interface configured to be coupled to a host device, to receive data from the host device, and to send data to the host device. In certain aspects, the data storage system includes a primary compression engine configured to compress data received from the host device via the host interface, and a secondary compression engine configured to decompress and compress data associated with operations internal to the data storage system. In some implementations, the data storage systems can further include a processor configured to transfer data between the host interface and the primary compression engine, between the primary compression engine and a non-volatile storage medium, between a memory and the secondary compression engine, and between the secondary compression engine and the memory. A data storage system is also provided.

Abstract: A method for partial fingerprint recognition, the method comprising the steps of extracting features including ridge orientations, valley images, minutiae, and pores from at least two fingerprint fragments, aligning the fingerprint fragments, matching the pores and minutiae on the fingerprint fragments after applying estimated alignment transformation, calculating a final matching score based on a pore matching score and a minutiae matching score, identifying a person based on a result of the final matching score.

Abstract: A data storage system includes a host interface configured to be coupled to a host device, to receive data from the host device, and to send data to the host device and a memory. The data storage system further includes a primary compression engine coupled to the host interface and to the memory, wherein the primary compression engine is configured to compress data received from the host device via the host interface and to store the compressed data in the memory, and wherein the primary compression engine is further configured to decompress compressed data stored in the memory prior to the decompressed data being sent to the host device via the host interface.

Abstract: A data storage system includes a host interface configured to be coupled to a host device, to receive data from the host device, and to send data to the host device and a memory. The data storage system further includes a primary compression engine coupled to the host interface and to the memory, wherein the primary compression engine is configured to compress data received from the host device via the host interface and to store the compressed data in the memory, and wherein the primary compression engine is further configured to decompress compressed data stored in the memory prior to the decompressed data being sent to the host device via the host interface.

Abstract: A biometric identification system (30) for identifying a person, the system (30) comprising: an image acquisition module (31) to capture a three-dimensional (3D) image of a palm of the person; a region of interest (ROI) extraction module (34) to extract a 3D subimage from the captured image; and a 3D features extraction module (36) to extract 3D palmprint features from the 3D subimage; wherein the extracted 3D palmprint features are compared to reference 3D palmprint features to verify the identity of the person.

Abstract: A method for palmprint verification of an individual that includes illuminating a palm of an individual with a plurality of spectral bands, collecting a plurality of palmprint images that are illuminated under the different spectral bands, locating a sub-image from each of the plurality of palmprint images, extracting palmprint feature maps from the sub-images, determining a palmprint matching score for each of the spectral bands based on the palmprint feature maps, computing a fused score by combining at least two of the palmprint matching scores under different spectral bands, without double-counting overlapping regions, and comparing the fused score with a threshold score from a database.

Abstract: A method of personal identification includes switching between visible and near infrared light, acquiring palmprint image and palm vein image from a person under the visible and the near infrared light, extracting sub-images from the palmprint image and the palm vein image based on a region of interest, extracting multiple features from the sub-images, and matching the extracted multiple features with stored information in a database to authenticate the person.

Abstract: A method of personal identification includes switching between visible and near infrared light, acquiring palmprint image and palm vein image from a person under the visible and the near infrared light, extracting sub-images from the palmprint image and the palm vein image based on a region of interest, extracting multiple features from the sub-images, and matching the extracted multiple features with stored information in a database to authenticate the person.

Abstract: A method for partial fingerprint recognition, the method comprising the steps of extracting features including ridge orientations, valley images, minutiae, and pores from at least two fingerprint fragments, aligning the fingerprint fragments, matching the pores and minutiae on the fingerprint fragments after applying estimated alignment transformation, calculating a final matching score based on a pore matching score and a minutiae matching score, identifying a person based on a result of the final matching score.

Abstract: A biometric identification system (30) for identifying a person, the system (30) comprising: an image acquisition module (31) to capture a three-dimensional (3D) image of a palm of the person; a region of interest (ROI) extraction module (34) to extract a 3D subimage from the captured image; and a 3D features extraction module (36) to extract 3D palmprint features from the 3D subimage; wherein the extracted 3D palmprint features are compared to reference 3D palmprint features to verify the identity of the person.

Abstract: A method of biometrics identification includes obtaining an image including a portion of a hand of an individual, analyzing the image to find one or more feature parameters defining different characteristics of the hand, and comparing the feature parameters with reference information in a database. The features parameters including a geometrical features parameter, a palm line features parameter or a palm texture features parameter.

Abstract: A method of biometrics identification includes obtaining an image including a portion of a hand of an individual, analyzing the image to find one or more feature parameters defining different characteristics of the hand, and comparing the feature parameters with reference information in a database. The features parameters including a geometrical features parameter, a palm line features parameter or a palm texture features parameter.

Abstract: A digital processing apparatus and method for executing a turbo coding routine. The apparatus and method includes adapting a turbo coding algorithm for execution by one or more reconfigurable processing elements from an array of processing elements, and then mapping the adapted algorithm onto the array for execution. A method includes configuring a portion of an array of independently reconfigurable processing elements for performing a turbo coding routine, and executing the turbo coding routine on data blocks received at the configured portion of the array of processing elements. An apparatus includes an array of interconnected, reconfigurable processing elements, where each processing element is independently programmable with a context instruction.

Abstract: A method and apparatus for convolution encoding and Viterbi decoding utilizes a flexible, digital signal processing architecture that comprises a core processor and a plurality of re-configurable processing elements arranged in a two-dimensional array. The core processor is operable to configure the re-configurable processing elements to perform data encoding and data decoding functions. A received data input is encoded by configuring one of the re-configurable processing elements to emulate a convolution encoding algorithm and applying the received data input to the convolution encoding algorithm. A received encoded data input is decoded by configuring the plurality of re-configurable processing elements to emulate a Viterbi decoding algorithm wherein the plurality of re-configurable processing elements is configured to accommodate every data state of the convolution encoding algorithm.

Abstract: A method and apparatus for convolution encoding and Viterbi decoding utilizes a flexible, digital signal processing architecture that comprises a core processor and a plurality of re-configurable processing elements arranged in a two-dimensional array. The core processor is operable to configure the re-configurable processing elements to perform data encoding and data decoding functions. A received data input is encoded by configuring one of the re-configurable processing elements to emulate a convolution encoding algorithm and applying the received data input to the convolution encoding algorithm. A received encoded data input is decoded by configuring the plurality of re-configurable processing elements to emulate a Viterbi decoding algorithm wherein the plurality of re-configurable processing elements is configured to accommodate every data state of the convolution encoding algorithm.