Sentence examples for using the fuzzy inference from inspiring English sources

Using the Fuzzy Inference System enables us to increase the visibility factor α in the less sensitivity areas (High texture, important contrast, and small homogeneity), while at the same time decreasing the value of the visibility factor in more sensitive areas (important homogeneity, small contrast, and small entropy).

Furthermore, this framework is developed using the fuzzy inference system toolbox of MATLAB, employing specifically the Mamdani algorithm with a triangular membership function.

Moreover, a fuzzy decision-making engine was developed to make the system more powerful for attack detection, using the fuzzy inference approach.

This adaptive embedding strength is generated using the Fuzzy Inference System which takes HVS characteristics such as luminance, texture and edge of each frame as an input in the DWT transform.

The results show: the functions of the gain fuzzy controller based on FPGA are implemented correctly, and the design is effectively simplified, and the real-time performance is improved by using the fuzzy inference lookup table.

The IoC machine, estimating the anesthesia index by using the fuzzy inference algorithm, also shows the EMG bar and burst suppression ration (BSR).

For the real-time applicability, a computationally efficient version of the proposed receiver is derived based on the least-mean-square (LMS) algorithm using the fuzzy-inference-controlled step-size.

In the signal processing module, the recursive least square (RLS) algorithm and the Kalman filter are exploited to extract the order amplitudes of vibration signals, followed by fault classification using the fuzzy state inference module.

The COMAC protocol is adaptable to drivers' behavior on the road and has a learning mechanism for predicting the future speed and position of all cluster members using the fuzzy logic inference system (FIS).

The proposed MAC protocol is adaptable to drivers' behavior on the road and has learning mechanism for predicting the future speed and position of all cluster members using the fuzzy logic inference system.

The high stability of COMAC results from its adaptability to drivers' behavior on the road and its learning process to predict the future speed and position of all cluster members using the fuzzy logic inference system.