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GFA in this study serves to select descriptors that were applied as input in multiple linear regression (MLR), multiple non-linear regression (MNLR) and applicability domain (AD).
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This paper presents multiple observer design for nonlinear chaotic systems with unknown inputs in multiple model approach.
Both steady state input multiplicity (i.e., multiple values of input resulting in one value of output) and output multiplicity (i.e., one value of input resulting in multiple values of output) are possible.
First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures.
These two methods are termed the 'individual model ensemble' and the other 'model ensemble Monte Carlo simulation' respectively, and both provide multiple change predictions derived from multiple AOGCMs as input, resulting in multiple realizations of possible future changes in coral cover using a variety of model parameters.
GSNAF has been shown to offer improved accuracy in benchmark classification scenarios and provide enhanced modeling accuracy in single input single output as well as in multiple input multiple output dynamic system identification cases.
Selected features can be introduced as inputs in a multiple regression model.
The proposed modulator can be used in multiple input and multiple output (MIMO) communication systems, where the receiver needs to rearrange the data in the correct order.
In [5], the optimal pilot symbol power in multiple input multiple output (MIMO) systems was derived based on a lower bound for capacity.
Coherent detection and equalization in multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM [1]) systems require channel state information (CSI) at the receiver.
Precoding techniques can be used in multiple input multiple output (MIMO) system to assign resources such as power and information optimally.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com