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A functional flow block diagram (FFBD) is a multi-tier, time-sequenced, step-by-step flow diagram of a system's functional flow. [2] The term "functional" in this context is different from its use in functional programming or in mathematics, where pairing "functional" with "flow" would be ambiguous. Here, "functional flow" pertains to the ...
Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into the TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers ...
The functional flow block diagram (FFBD) is a multi-tier, time-sequenced, step-by-step flow diagram of the system's functional flow. [14] The diagram is developed in the 1950s and widely used in classical systems engineering. The functional flow block diagram is also referred to as Functional Flow Diagram, functional block diagram, and ...
A multiple timescales recurrent neural network (MTRNN) is a neural-based computational model that can simulate the functional hierarchy of the brain through self-organization depending on the spatial connection between neurons and on distinct types of neuron activities, each with distinct time properties.
A control-flow diagram can consist of a subdivision to show sequential steps, with if-then-else conditions, repetition, and/or case conditions. Suitably annotated geometrical figures are used to represent operations, data, or equipment, and arrows are used to indicate the sequential flow from one to another.
Where a sequential program can be imagined as a single worker moving between tasks (operations), a dataflow program is more like a series of workers on an assembly line, each doing a specific task whenever materials are available. Since the operations are only concerned with the availability of data inputs, they have no hidden state to track ...
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.
Sequential consistency is the property of a program that its execution produces the same results as a sequential program. Specifically, a program is sequentially consistent if "the results of any execution is the same as if the operations of all the processors were executed in some sequential order, and the operations of each individual ...