Heuristics for deriving adaptive homing and distinguishing sequences for nondeterministic finite state machines

In particular, under strong mixing conditions, we prove that our hard thresholding estimator attains a particular rate of convergence: the optimal one in the i.i.d.. The one of 0

1) A feature selection scheme is proposed for effective signal feature processing. Discriminant- and correlation-based feature selections are integrated to obtain feature

The time complexity of the unary exact real algorithm which computes a M¨ obius transformation depends on the growth of its inner state matrices during the computation.. Heckmann

Graph-based slicing that eliminates unnecessary tran- sitions and nodes produces an output that will not be a sub graph of the original. Although we term this amorphous slicing it

The heuristic search results suggest that combining the search for feasible transi- tion paths (FTPs), examined in Chapter 4, and the search for unique input /output sequences

The smallest locally s-equivalent FSM defines the set of traces of the specification that must be implemented in order for the system under test (SUT) not to be distinguishable from

to symbolic input finite state machine (SIFSM). SIFSM [21] is an extension of FSM with inputs specified with predicates on input variables possibly having infinite do- mains,

propose a complete model-based equivalence testing strategy applicable to reac- tive systems with large, possibly infinite input data types but finite internal and output data..