A memory array arranged in multiple columns and rows. Computation circuits that each calculate a computation value from cell values in a corresponding column. A column multiplexer cycles through multiple data lines that each corresponds to a computation circuit. Cluster cycle management circuitry determines a number of multiplexer cycles based on a number of columns storing data of a compute cluster. A sensing circuit obtains the computation values from the computation circuits via the column multiplexer as the column multiplexer cycles through the data lines. The sensing circuit combines the obtained computation values over the determined number of multiplexer cycles. A first clock may initiate the multiplexer to cycle through its data lines for the determined number of multiplexer cycles, and a second clock may initiate each individual cycle. The multiplexer or additional circuitry may be utilized to modify the order in which data is written to the columns.

An autonomous tilting three-wheeled vehicle comprises a pair of front wheels coupled to a tiltable chassis by a mechanical linkage, such that the pair of wheels and the chassis are configured to tilt in unison with respect to a roll axis of the chassis. An electronic controller of the autonomous vehicle controls a tilt actuator to selectively tilt the chassis. Optionally, a steering actuator is coupled to the front wheels and controlled by the electronic controller to selectively steer the wheels. A sensor configured to measure orientation-dependent information may be coupled to the chassis by a gimbal configured to compensate for vehicle tilt. In some examples, the autonomous vehicle comprises an autonomous delivery robot.

The technology disclosed relates to simplifying updating of a predictive model using clustering observed points. In particular, it relates to observing a set of points in 3D sensory space, determining surface normal directions from the points, clustering the points by their surface normal directions and adjacency, accessing a predictive model of a hand, refining positions of segments of the predictive model, matching the clusters of the points to the segments, and using the matched clusters to refine the positions of the matched segments. It also relates to distinguishing between alternative motions between two observed locations of a control object in a 3D sensory space by accessing first and second positions of a segment of a predictive model of a control object such that motion between the first position and the second position was at least partially occluded from observation in a 3D sensory space.

A first multiplex circuit generates a first multiplex signal obtained by time-divisionally multiplexing a first real part and a first imaginary part of a first complex number. A second multiplex circuit generates a second multiplex signal obtained by time-divisionally multiplexing a second real part and a second imaginary part of a second complex number. A multiply-subtract operation circuit performs a multiply-subtract operation of the first and second multiplex signals. A third multiplex circuit generates a third multiplex signal obtained by time-divisionally multiplexing the first and second real parts. A fourth multiplex circuit generates a fourth multiplex signal obtained by time-divisionally multiplexing the first and second imaginary parts. A multiply-accumulate operation circuit performs a multiply-accumulate operation of the third and fourth multiplex signals. A fifth multiplex circuit generates a fifth multiplex signal obtained by time-divisionally multiplexing output values of the multiply-subtract operation circuit and the multiply-accumulate operation circuit.

A first multiplex circuit generates a first multiplex signal obtained by time-divisionally multiplexing a first real part and a first imaginary part of a first complex number. A second multiplex circuit generates a second multiplex signal obtained by time-divisionally multiplexing a second real part and a second imaginary part of a second complex number. A multiply-subtract operation circuit performs a multiply-subtract operation of the first and second multiplex signals. A third multiplex circuit generates a third multiplex signal obtained by time-divisionally multiplexing the first and second real parts. A fourth multiplex circuit generates a fourth multiplex signal obtained by time-divisionally multiplexing the first and second imaginary parts. A multiply-accumulate operation circuit performs a multiply-accumulate operation of the third and fourth multiplex signals. A fifth multiplex circuit generates a fifth multiplex signal obtained by time-divisionally multiplexing output values of the multiply-subtract operation circuit and the multiply-accumulate operation circuit.

The present invention belongs to the technical field of signal processing, and relates to an online fast processing method for real-time data based on edge computing. In the present invention, a dynamic online de-noising method is adopted to remove noise contained in speeds to ensure the effectiveness and accuracy of de-noising results; for the displacement integrated online, an efficient method is adopted for dynamic online de-noising to further reduce the effectiveness of drift in the displacement value on final integration results; and under the condition of ensuring the accuracy of an integration method, an integration algorithm is embedded into an edge device to realize fast calculation and analysis of data near a data source and realize dynamic fast integration of online signals based on edge computing, which provides effective references for efficient processing and calculation of data.

The present invention belongs to the technical field of signal processing, and relates to an online fast processing method for real-time data based on edge computing. In the present invention, a dynamic online de-noising method is adopted to remove noise contained in speeds to ensure the effectiveness and accuracy of de-noising results; for the displacement integrated online, an efficient method is adopted for dynamic online de-noising to further reduce the effectiveness of drift in the displacement value on final integration results; and under the condition of ensuring the accuracy of an integration method, an integration algorithm is embedded into an edge device to realize fast calculation and analysis of data near a data source and realize dynamic fast integration of online signals based on edge computing, which provides effective references for efficient processing and calculation of data.

Techniques herein minimally communicate between computers to repartition a graph. In embodiments, each computer receives a partition of edges and vertices of the graph. For each of its edges or vertices, each computer stores an intermediate representation into an edge table (ET) or vertex table. Different edges of a vertex may be loaded by different computers, which may cause a conflict. Each computer announces that a vertex resides on the computer to a respective tracking computer. Each tracking computer makes assignments of vertices to computers and publicizes those assignments. Each computer that loaded conflicted vertices transfers those vertices to computers of the respective assignments. Each computer stores a materialized representation of a partition based on: the ET and vertex table of the computer, and the vertices and edges that were transferred to the computer. Edges stored in the materialized representation are stored differently than edges stored in the ET.

Techniques herein minimally communicate between computers to repartition a graph. In embodiments, each computer receives a partition of edges and vertices of the graph. For each of its edges or vertices, each computer stores an intermediate representation into an edge table (ET) or vertex table. Different edges of a vertex may be loaded by different computers, which may cause a conflict. Each computer announces that a vertex resides on the computer to a respective tracking computer. Each tracking computer makes assignments of vertices to computers and publicizes those assignments. Each computer that loaded conflicted vertices transfers those vertices to computers of the respective assignments. Each computer stores a materialized representation of a partition based on: the ET and vertex table of the computer, and the vertices and edges that were transferred to the computer. Edges stored in the materialized representation are stored differently than edges stored in the ET.

Methods of designing a polynucleotide sequence for expressing a polypeptide-of-interest in a cell are provided. Also provided are artificial transcript sequences generated according to the present teachings. Further provided are methods of estimating the adaptiveness of a transcript sequence encoding a polypeptide-of-interest to a gene expression machinery in a cell.