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This recommended practice defines signal processing algorithms and data structure in order to share and to infer signal and state information of an instrument or control system. These algorithms are based on their own signal and also on the transducers attached to the system. The recommended practice also defines the commands and replies for requesting information and algorithms for shape analysis such as exponential, sinusoidal, impulsive noise, noise, and tendency.
The purpose is to define a standardized and universal framework that allows smart transducers to extract features of the signal being generated and measured. With the definition of these practices, the raw data can be converted into information and then into knowledge. In this context, knowledge means understanding of the nature of the transducer signal. This understanding can be shared with the system and other transducers in order to form a platform for sensory knowledge fusion.
New IEEE Standard - Active. Signal processing algorithms and data structure are defined in this recommended practice in order to share and to infer signal and state information of an instrumentation or control system. These algorithms are based on the signal and transducers attached to the system. This recommended practice also defines a set of transducer signal treatment services based on signal treatment algorithms as application programming interface (API), which is used for applications to use or call these transducer signal treatment services.