In this work we introduce a variable step-size normalized LMS algorithm for adaptive echo cancellation in a FIRstructure. In the proposed scheme, the step-size adjustment is controlled by using the square of the cross-correlationbetween the squared output error and the adaptive filter output. The proposed algorithm (that we call VSSSC aftervariable step size based on the squared cross-correlation) was evaluated using white noise and speech signals.Simulation results show that our proposal achieves better performance than similar algorithms in single and doubletalk. The proposed algorithm can be used in a number of applications such as in echo reduction for long-haul voicecommunications.
This article presents a prototype called PMIIDAS. The prototype focuses on the creation of open educational resources based on pedagogical and institutional guidelines, their representation using semantic indexing, and the storage and retrieval thereof by Semantic Web technologies. The use of this prototype can have benefits such as the reuse of open educational resources, which are distributed in institutional repositories or educational platforms by applying a semantic approach, search and retrieval of relevant information can be done through the use of ontologies and user profiles; as well as the exchange of educational resources among educational institutions.
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