Dynamic Filtering of Ranked Answers When Evaluating Fuzzy XPath Queries

2014 ◽  
pp. 319-330 ◽  
Author(s):  
Jesús M. Almendros-Jiménez ◽  
Alejandro Luna Tedesqui ◽  
Ginés Moreno
Keyword(s):  
Dynamic Filtering

scholarly journals Dynamic filtering improves attentional state prediction with fNIRS

2016 ◽  
Vol 7 (3) ◽  
pp. 979 ◽  
Author(s):  
Angela R. Harrivel ◽  
Daniel H. Weissman ◽  
Douglas C. Noll ◽  
Theodore Huppert ◽  
Scott J. Peltier
Keyword(s):  
Attentional State ◽  
State Prediction ◽  
Dynamic Filtering

Review and comparative evaluation of symbolic dynamic filtering for detection of anomaly patterns

2008 ◽  
Vol 3 (2) ◽  
pp. 101-114 ◽  
Author(s):  
Chinmay Rao ◽  
Asok Ray ◽  
Soumik Sarkar ◽  
Murat Yasar
Keyword(s):  
Comparative Evaluation ◽  
Symbolic Dynamic ◽  
Symbolic Dynamic Filtering ◽  
Dynamic Filtering

A novel improved CKF with adaptive generation of the cubature points and weights for target tracking

2021 ◽  
Author(s):  
Hongpo Fu ◽  
Yongmei Cheng ◽  
Cheng Cheng
Keyword(s):  
Target Tracking ◽  
Superior Performance ◽  
Inner Product ◽  
Estimation Accuracy ◽  
Cubature Rule ◽  
Cubature Kalman Filter ◽  
One Step ◽  
Tracking Model ◽  
Dynamic Filtering ◽  
High Degree

Abstract In the nonlinear state estimation, the generation method of cubature points and weights of the classical cubature Kalman filter (CKF) limits its estimation accuracy. Inspired by that, in this paper, a novel improved CKF with adaptive generation of the cubature points and weights is proposed. Firstly, to improve the accuracy of classical CKF while considering the calculation efficiency, we introduce a new high-degree cubature rule combining third-order spherical rule and sixth-degree radial rule. Next, in the new cubature rule, a novel method that can generate adaptively cubature points and weights based on the distance between the points and center point in the sense of the inner product is designed. We use the cosine similarity to quantify the distance. Then, based on that, a novel high-degree CKF is derived that use much fewer points than other high-degree CKF. In the proposed filter, based on the actual dynamic filtering process, the simultaneously adaptive generation of cubature points and weight can make the filter reasonably distribute the cubature points and allocate the corresponding weights, which can obviously improve the approximate accuracy of one-step state and measurement prediction. Finally, the superior performance of the proposed filter is demonstrated in a benchmark target tracking model.

scholarly journals Complex signal processing in synthetic gene circuits using cooperative regulatory assemblies

Science ◽  
2019 ◽  
Vol 364 (6440) ◽  
pp. 593-597 ◽  
Author(s):  
Caleb J. Bashor ◽  
Nikit Patel ◽  
Sandeep Choubey ◽  
Ali Beyzavi ◽  
Jané Kondev ◽  
...  
Keyword(s):  
Signal Processing ◽  
Self Assembly ◽  
Design Principle ◽  
Complex Signal ◽  
Synthetic Gene Circuits ◽  
Cellular Decision Making ◽  
Eukaryotic Genes ◽  
Transcription Factor Complexes ◽  
Dynamic Filtering ◽  
Cooperative Assembly

Eukaryotic genes are regulated by multivalent transcription factor complexes. Through cooperative self-assembly, these complexes perform nonlinear regulatory operations involved in cellular decision-making and signal processing. In this study, we apply this design principle to synthetic networks, testing whether engineered cooperative assemblies can program nonlinear gene circuit behavior in yeast. Using a model-guided approach, we show that specifying the strength and number of assembly subunits enables predictive tuning between linear and nonlinear regulatory responses for single- and multi-input circuits. We demonstrate that assemblies can be adjusted to control circuit dynamics. We harness this capability to engineer circuits that perform dynamic filtering, enabling frequency-dependent decoding in cell populations. Programmable cooperative assembly provides a versatile way to tune the nonlinearity of network connections, markedly expanding the engineerable behaviors available to synthetic circuits.

Sign in / Sign up

Export Citation Format

Share Document