A Worst-Case Execution Time Analysis Approach Based on Independent Paths for ARM Programs

To overcome disadvantages of traditional worst-case execution time （WCET） analysis approaches, we propose a new WCET analysis approach based on independent paths for ARM programs. Based on the results of program flow analysis, it reduces and partitions the control flow graph of the program and obtains a directed graph. Using linear combinations of independent paths of the directed graph, a set of feasible paths can be generated that gives complete coverage in terms of the program paths considered. Their timing measurements and execution counts of program segments are derived from a limited number of measurements of an instrumented version of the program. After the timing measurement of the feasible paths are linearly expressed by the execution times of program seg-ments, a system of equations is derived as a constraint problem, from which we can obtain the execution times of program segments. By assigning the execution times of program segments to weights of edges in the directed graph, the WCET estimate can be calculated on the basis of graph-theoretical techniques. Comparing our WCET estimate with the WCET measurement obtained by the exhaustive measurement, the maximum error ratio is only 8.259 3 %. It is shown that the proposed approach is an effective way to obtain the safe and tight WCET estimate for ARM programs.

Optimal gear shift control strategy for positive independent mechanical split path transmission with automatic shift system

An improvement strategy which controls the shift effort and the power summing planetary gear set of steering clutches and brakes have been proposed based on the dynamic model of synchroniser in order to decrease the wear of synchroniser inserts, make gear shift easy and reduce the shock noise for a positive independent mechanical split path transmission which attached an auto- matic shift system when shifting. A kinetics model for the process of synchroniser engagement is built and analyzed in the paper. Thus for optimizing the gear shift process which is divided into three phases a model reference fuzzy self-adaption system is adopted. Through a 6 000 km road experiment, the control strategy has proved feasible and dependable.

The Researches on Path Independence Problem

Rationality condition is imposed in Arrow's General Possibility Theorem in order for social choice to be independent of the path of choice. In this Paper, emphasis is laid on the analysis of the relevance of path independence and rationality condition. Two kinds of Path independence, i.e., Plott's path independence and Bandyopadhyay's sequential path independence, are shown, and their meanings with respect to the problem are investigated.

An Approach to the Fault Diagnosis and Testability in Analog Circuits at Module Level

In this paper, a module level fault diagnosis method is presented which considers multi-port device or subnetwork as the basic unit. The fault model in this method is quite similar to an actual condition,hence it has practical meaning. The equations of moedule level fault diagnosis are derived, and thetestability problem for module-fault diagnosis is discussed in general. The paper then gives severaltoplolgical conditions for module-fault testubility, which are applicable to a general nonreciprocal network by introducing a generalized independent path.

Interpreting the Basis Path Set in Neural Networks

The G-SGD algorithm significantly outperforms the conventional SGD algorithm in ReLU neural networks by adopting the basis path set.However,how the inner mechanism of basis paths works remains mysterious,and the G-SGD algorithm that helps to find a basis path set is heuristic.This paper employs graph theory to investigate structure properties of basis paths in a more general and complicated neural network with unbalanced layers and edge-skipping.The hierarchical Algorithm HBPS is proposed to find a basis path set,by decomposing the complicated network into several independent and parallel substructures.The paper theoretically extends the study of basis paths and provides one methodology to find the basis path set in a more general neural network.

Path independence of the additive functionals for stochastic differential equations driven by G-lévy processes

In this study,we are interested in stochastic differential equations driven by GLévy processes.We illustrate that a certain class of additive functionals of the equations of interest exhibits the path-independent property,generalizing a few known findings in the literature.The study is ended with many examples.