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A MATLAB function can be developed to represent a task-scheduling sequence, routing of parts, or production recipes in a process flow. Since the two programs are within the same tools environment, it is straightforward to generate custom random distributions of input tasks, optimize a process, as well as to generate custom statistics.
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MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. Although MATLAB is intended primarily for numeric computing, an optional toolbox uses the MuPAD symbolic engine allowing access to symbolic computing abilities.
The original specification included a binary header, and used an event table. [3] An updated specification (GDF v2) was released in 2011 and added fields for additional subject-specific information (gender, age, etc.) and utilized several standard codes for storing physical units and other properties. [2]
The company's two lead products are MATLAB, which provides an environment for scientists, engineers and programmers to analyze and visualize data and develop algorithms, and Simulink, a graphical and simulation environment for model-based design of dynamic systems.
Transfer entropy is a non-parametric statistic measuring the amount of directed (time-asymmetric) transfer of information between two random processes. [1] [2] [3] Transfer entropy from a process X to another process Y is the amount of uncertainty reduced in future values of Y by knowing the past values of X given past values of Y.
In computing, the count–min sketch (CM sketch) is a probabilistic data structure that serves as a frequency table of events in a stream of data.It uses hash functions to map events to frequencies, but unlike a hash table uses only sub-linear space, at the expense of overcounting some events due to collisions.
Each event occurs at a particular instant in time and marks a change of state in the system. [1] Between consecutive events, no change in the system is assumed to occur; thus the simulation time can directly jump to the occurrence time of the next event, which is called next-event time progression.