Sentence examples for based on these functions from inspiring English sources

Based on these functions, we developed two low-level applications: (1) particle filter-based human localization and tracking using wearable motion sensors and distributed binary sensors; (2) Dynamic Bayesian Network-based human activity recognition using microphones and distributed binary sensors.

Evaluation of the environmental noise based on these functions is another feature of this system.

Based on these functions, the nodes in AMI are always irregularly distributed and the communication is low data rate and short range.

In addition to regulatory functions like those in Eq. (1), a logical model must also specify how the node state variables change with time based on these functions, that is, we need to specify an updating scheme.

As an example, we consider f ( N t ) : = 1 N t + 1 and α : = α ( N t ) = N t N t + α. Figure 1 shows a graph which demonstrates the dynamics of the population model based on these functions with and without the Allee effect with respect to time for different values of r.

In this paper we propose new classes of kernel functions whose form is different from known kernel functions and define interior-point methods (IPMs) based on these functions whose barrier term is exponential power of exponential functions for P ∗ -horizontal linear complementarity problems (HLCPs).

Based on these feature functions, we define the joint density function of 1471-2164-13-S2-S5 as, (2) p (X | θ X ) = 1 Δ e x p (∑ i, j, W i j = 1, k ∈ { 1, 2, ⋯, 7 } γ k F k (X i j ) ) In the above equation γ k, k ∈ {1, 2,... 7} are the coefficients of the seven feature functions in MRF.

Based on these known functions of BIN1, we hypothesized that DNM2-S619L mutations function to impair triad structure by interfering with BIN1-mediated tubulogenesis.

Based on these multiple functions, legume crops have high potential for conservation agriculture, being functional either as growing crop or as crop residue.

The neuron models based on these aggregation functions ensure faster convergence, better training, and prediction accuracy.

Finally, we derive the framework for analyzing the iteration bounds and the complexity results of the algorithms based on these kernel functions in Section 4.