Abstract: Embodiments of the present invention provide several long training sequences that are in a wireless local area network and that comply with 802.11ax.

Abstract: Aspects of the present disclosure are directed to devices and methods for performing MAC operations using a TCAM array as a compute-in-memory (CIM) device that can enable higher computational throughput, higher performance and lower energy consumption compared to computation using a processor outside of a memory array. In some embodiments, weights in a weight matrix may be programmed in SRAMs of a TCAM bit cell array. Each SRAM may operate as a multiplier that performs a multiplication between the stored weight to an input activation value applied at a search line in the TCAM bit cell array. The two SRAMs within a TCAM bit cell may operate independently to receive independently two input activation values on their respective select lines, and to perform a multiplication operation with the stored weight in each respective SRAM.

Abstract: An input-shaping method for a group-modulated input scheme in a plurality of computing-in-memory applications is configured to shape a plurality of multi-bit input signals. The input-shaping method for the group-modulated input scheme in the plurality of computing-in-memory applications includes performing an input splitting step, a threshold setting step and an input shaping step. The input splitting step includes splitting the multi-bit input signals into a plurality of input sub-groups via an input-shaping unit. The threshold setting step includes setting at least one shaping threshold via the input-shaping unit. The input shaping step includes shaping at least one of the input sub-groups according to the at least one shaping threshold via the input-shaping unit to form a plurality of shaped multi-bit input signals so as to increase a probability of a bit equal to 0 occurring in the at least one of the input sub-groups.

Abstract: A system includes a global generator and local generators. The global generator is coupled to a memory array, and is configured to generate global signals, according to a number of a computational output of the memory array. The local generators are coupled to the global generator and the memory array, and are configured to generate local signals, according to the global signals. Each one of the local generators includes a first reference circuit and a local current mirror. The first reference circuit is coupled to the global generator, and is configured to generate a first reference signal at a node, in response to a first global signal of the global signals. The local current mirror is coupled to the first reference circuit at the node, and is configured to generate the local signals, by mirroring a summation of at least one signal at the node.

Abstract: A memory unit with an asymmetric group-modulated input scheme and a current-to-voltage signal stacking scheme for a plurality of non-volatile computing-in-memory applications is configured to compute a plurality of multi-bit input signals and a plurality of weights. A controller splits the multi-bit input signals into a plurality of input sub-groups and generates a plurality of switching signals according to the input sub-groups, and the input sub-groups are sequentially inputted to the word lines. The current-to-voltage signal stacking converter converts the bit-line current from a plurality of non-volatile memory cells into a plurality of converted voltages according to the input sub-groups and the switching signals, and the current-to-voltage signal stacking converter stacks the converted voltages to form an output voltage. The output voltage is corresponding to a sum of a plurality of multiplication values which are equal to the multi-bit input signals multiplied by the weights.

Abstract: A memory unit with an asymmetric group-modulated input scheme and a current-to-voltage signal stacking scheme for a plurality of non-volatile computing-in-memory applications is configured to compute a plurality of multi-bit input signals and a plurality of weights. A controller splits the multi-bit input signals into a plurality of input sub-groups and generates a plurality of switching signals according to the input sub-groups, and the input sub-groups are sequentially inputted to the word lines. The current-to-voltage signal stacking converter converts the bit-line current from a plurality of non-volatile memory cells into a plurality of converted voltages according to the input sub-groups and the switching signals, and the current-to-voltage signal stacking converter stacks the converted voltages to form an output voltage. The output voltage is corresponding to a sum of a plurality of multiplication values which are equal to the multi-bit input signals multiplied by the weights.

Abstract: The present invention discloses a prediction method for system errors, applied in prediction system predicting system errors of a monitored system. The method comprises steps of: pre-processing training data formed with data points at time slots to generate corresponding features to the data points of each time slot, and extract a frequency-based feature for each time slot according to distribution of clustering, grouping or classification of the corresponding features in the previous time slot of the current time slot. Using machine learning algorithm and taking model building data coming from the corresponding features and frequency-based feature as input to build up a prediction model for predicting and alerting a future error of the monitored system.

Abstract: A memory unit with multiple word lines for a plurality of non-volatile computing-in-memory applications is configured to compute a plurality of input signals and a plurality of weights. The memory unit includes a non-volatile memory cell array, a replica non-volatile memory cell array and a multi-row current calibration circuit. The non-volatile memory cell array is configured to generate a bit-line current. The replica non-volatile memory cell array includes a plurality of replica non-volatile memory cells and is configured to generate a calibration current. Each of the replica non-volatile memory cells is in the high resistance state. The multi-row current calibration circuit is electrically connected to the non-volatile memory cell array and the replica non-volatile memory cell array. The multi-row current calibration circuit is configured to subtract the calibration current from a dataline current to generate a calibrated dataline current. The dataline current is equal to the bit-line current.

Abstract: The present invention discloses a prediction method based on unstructured data, applied in a prediction system comprising an analyzing module and a model-building module to predict future behaviors of a user. The prediction method comprises steps of: with the analyzing module, analyzing a recording file with a natural language processing algorithm to generate at least one feature vector, wherein the recording file is related to a subject behavior in a predetermined observation period, at least one record in a form of unstructured data is stored therein, and the record comprises a time stamp and a recording text; and with the model-building module, using a surprised machine learning algorithm building a model with information corresponding to the feature vector as input for predicting future behaviors of a user, wherein the record is one of query record of domain name system, transaction record of automated teller machine, transaction record of structured query language and literal record.

Abstract: A detective method, applied in a detective system comprising an activity-or-behavior model constructor, for activity-or-behavior model construction and automatic detection of activities of a subject system, comprises steps of using an unsupervised machine learning technique, a Natural Language Processing technique (NLP) and a supervised machine learning technique. As such, an activity-or-behavior model is built for predicting the future behaviors of the subject system and automatically detecting abnormal activities or behaviors of the subject system. The activity-or-behavior model is capable to handle multidimensional sensor data input from a plurality of sensor data streams and incorporate the sensor data values and a selected temporal information about at least one sensor data stream and between different sensor data streams.

Abstract: According to one embodiment of the invention, a method for detecting driving anomalies comprises steps of: with at least one algorithm, processing raw data from On-Board Diagnostics of a car to generate time-series data, with the time series data as input, using an automatic driving behavior separating technology to identify a plurality of driving behaviors; with the driving behaviors as input, using an artificial intelligence technology to build up a driving anomaly detection model without labeling the driving behaviors; and issuing an alarm for driving anomaly identified according to an analyzing result of alarm signature of the driving behaviors.

Abstract: Embodiments of the present invention provide several long training sequences that are in a wireless local area network and that comply with 802.11 ax.

Abstract: A memory unit is controlled by a word line, a reference voltage and a bit-line clamping voltage. A non-volatile memory cell is controlled by the word line and stores a weight. A clamping module is electrically connected to the non-volatile memory cell via a bit line and controlled by the reference voltage and the bit-line clamping voltage. A clamping transistor of the clamping module is controlled by the bit-line clamping voltage to adjust a bit-line current. A cell detector of the clamping module is configured to detect the bit-line current to generate a comparison output according to the reference voltage. A clamping control circuit of the clamping module switches the clamping transistor according to the comparison output and the bit-line clamping voltage. When the clamping transistor is turned on by the clamping control circuit, the bit-line current is corresponding to the bit-line clamping voltage multiplied by the weight.

Abstract: An anomaly flow detection device and an anomaly flow detection method thereof are provided.

Abstract: An HE-LTF transmission method is provided, including: determining, based on a total number NSTS of space-time streams, a number NHELTF of OFDM symbols included in an HE-LTF field; determining a HE-LTF sequence in frequency domain according to a transmission bandwidth and a mode of the HE-LTF field, where the HE-LTF sequence in frequency domain includes but is not limited to a mode of the HE-LTF field sequence that is in a 1× mode and that is mentioned in implementations; and sending a time-domain signal according to the number NHELTF of OFDM symbols and the determined HE-LTF sequence in frequency domain. In the foregoing solution, a PAPR value is relatively low.

Abstract: A data communication method and a related apparatus are provided, and the data communication method includes: constructing, by an access device, a beacon frame, where the beacon frame includes a newly added field, and the newly added field represents multiple data guard interval lengths supported by the access device; and broadcasting, by the access device, the beacon frame, so that a terminal selects an available guard interval length matching a data guard interval length supported by the terminal from the beacon frame, and performs data communication with the access device by using the available guard interval length. By using the present invention, data communication between the access device and the terminal can be implemented when the access device supports multiple data guard interval lengths.

Abstract: An HE-LTF transmission method is provided, including: determining, based on a total number NSTS of space-time streams, a number NHELTF of OFDM symbols included in an HE-LTF field; determining a HE-LTF sequence in frequency domain according to a transmission bandwidth and a mode of the HE-LTF field, where the HE-LTF sequence in frequency domain includes but is not limited to a mode of the HE-LTF field sequence that is in a 1× mode and that is mentioned in implementations; and sending a time-domain signal according to the number NHELTF of OFDM symbols and the determined HE-LTF sequence in frequency domain. In the foregoing solution, a PAPR value is relatively low.

Abstract: An electronics module is provided. The electronics module includes a housing at least partially enclosing a first printed circuit board configured to couple the electronics module to a connector attached to a second printed circuit board. The electronics module includes a first heat sink disposed along a first surface of the housing and a second heat sink disposed along a second surface of the housing. One or more notches or apertures of the first printed circuit board are proximate to the connector thereby enabling an airflow through the second heat sink along the second surface of the housing to exhaust over a surface of the connector with an airflow through the first heat sink.

Abstract: An access device constructs a beacon frame, where the beacon frame includes a newly added field, and the newly added field represents multiple data guard interval lengths supported by the access device. The access device broadcasts the beacon frame, so that a terminal selects an available guard interval length matching a data guard interval length supported by the terminal from the beacon frame, and performs data communication with the access device by using the available guard interval length. Data communication between the access device and the terminal can be implemented when the access device supports multiple data guard interval lengths.

Abstract: The embodiments of the present disclosure disclose a self-service express cabinet and a package delivery method. The self-service express cabinet may include: a cabinet body including a sending window and a chamber, wherein the sending window may be connected with the chamber, and the sending window may be disposed on a surface of the cabinet body; a human-machine interaction device disposed on the cabinet body for information interaction with a user; an inspection device disposed in the chamber and capable of performing security inspection on a package dropped into the chamber for delivery, wherein the inspection device may have a receiving end and an output end, and at least part of the receiving end may be located within a scope of a forward projection of the sending window; and at least one storage component disposed in the chamber and corresponding to the output end.