Brno University of Technology

About: Brno University of Technology is a education organization based out in Brno, Czechia. It is known for research contribution in the topics: Computer science & Fracture mechanics. The organization has 6339 authors who have published 15226 publications receiving 194088 citations. The organization is also known as: Vysoké učení technické v Brně & BUT.

Abstract regular tree model checking of complex dynamic data structures

Abstract: We consider the verification of non-recursive C programs manipulating dynamic linked data structures with possibly several next pointer selectors and with finite domain non-pointer data. We aim at checking basic memory consistency properties (no null pointer assignments, etc.) and shape invariants whose violation can be expressed in an existential fragment of a first order logic over graphs. We formalise this fragment as a logic for specifying bad memory patterns whose formulae may be translated to testers written in C that can be attached to the program, thus reducing the verification problem considered to checking reachability of an error control line. We encode configurations of programs, which are essentially shape graphs, in an original way as extended tree automata and we represent program statements by tree transducers. Then, we use the abstract regular tree model checking framework for a fully automated verification. The method has been implemented and successfully applied on several case studies.

High-performance current differencing transconductance amplifier and its application in precision current-mode rectification

Abstract: A CMOS-based circuit for realization of high-performance current differencing transconductance amplifier (CDTA) is demonstrated. The proposed circuit offers the advantages of a wide frequency bandwidth and very small input terminal impedance. The results of circuit simulations and an application example are given to illustrate the advantages of the proposed circuit for precise high-frequency signal rectification.

Towards Lower Error Rates in Phoneme Recognition

Abstract: We investigate techniques for acoustic modeling in automatic recognition of context-independent phoneme strings from the TIMIT database. The baseline phoneme recognizer is based on TempoRAl Patterns (TRAP). This recognizer is simplified to shorten processing times and reduce computational requirements. More states per phoneme and bi-gram language models are incorporated into the system and evaluated. The question of insufficient amount of training data is discussed and the system is improved. All modifications lead to a faster system with about 23.6% relative improvement over the baseline in phoneme error rate.