Abstract
Adaptive embedded systems can achieve enhanced flexibility by performing run-time reconfiguration of hardware. This paper describes a method to generate at run-time new partial FPGA configurations corresponding to arithmetic expressions. This is achieved by merging available partial bitstreams of arithmetic components to produce a new partial bitstream for a specific FPGA area. The connections among the components are mapped to the switch matrices of the reconfigurable fabric, and the corresponding information is added to the new partial configuration. The proposed method was implemented for a Virtex-II Pro FPGA with a 300 MHz PowerPC 405 CPU. It was used to create partial configurations in less than 69 s for sets of arithmetic circuits with up to 25 components and 208 connections.

Abstract
The Erlang programming language is a concurrency oriented functional language, based on the notion of independent processes and uses message passing for communication between processes. It is specially adapted to the realization of highly reliable distributed systems. In this paper it is analyzed the use of the Erlang's computational paradigm for the design and implementation of application specific heterogeneous computational systems. The main objective is to use for the low level implementation the same computational model used in high level view of the system. This will allow an easier and faster design space exploration and optimization. © 2010 IEEE.

Abstract
Although resynthesis may seem a simple analysis/synthesis process, it is a quite complex task, even more when it comes to recreating a singing voice. This paper presents a system whose goal is to start with an original audio stream of someone singing and recreate the same performance (melody, phonetics, dynam-ics) using an internal vocal sound library (choir or solo voice). By extracting dynamics and pitch information, and looking for phonetic similarities between the original audio frames and the frames of the sound library, a completely new audio stream is created. The obtained audio results, although not perfect (mainly due to the existence of audio artifacts), show that this technologi-cal approach may become an extremely powerful audio tool.

Abstract
Although resynthesis may seem a simple analysis/synthesis process, it is a quite complex task, even more when it comes to recreating a singing voice. This paper presents a system whose goal is to start with an original audio stream of someone singing and recreate the same performance (melody, phonetics, dynam-ics) using an internal vocal sound library (choir or solo voice). By extracting dynamics and pitch information, and looking for phonetic similarities between the original audio frames and the frames of the sound library, a completely new audio stream is created. The obtained audio results, although not perfect (mainly due to the existence of audio artifacts), show that this technologi-cal approach may become an extremely powerful audio tool.

Abstract
In this paper we address the accurate estimation of the frequency of sinusoids of natural signals such as singing, voice or music. These signals are intrinsicly harmonic and are normally contaminated by noise. Taking the Cramér-Rao Lower Bound for unbiased frequency estimators as a reference, we compare the performance of several DFT-based frequency estimators that are non-iterative and that use the rectangular window or the Hanning window. Tests conditions simulate harmonic interference and two new ArcTan-based frequency estimators are also included in the tests. Conclusions are presented on the relative performance of the different frequency estimators as a function of the SNR. ©2010 IEEE.

Abstract
The accurate estimation of the frequency of sinusoids is a frequent problem in many signal processing problems including the real-time analysis of the singing voice. In this paper we rely on a single DFT magnitude spectrum in order to perform frequency estimation in a non-iterative way. Two new frequency estimation methods are derived that are matched to the time analysis window and that reduce the maximum absolute estimation error to about 0.1% of the bin width of the DFT. The performance of these methods is evaluated including the parabolic method as a reference, and considering the influence of noise. A combined model is proposed that offers higher noise robustness than that of a single model. ©2010 IEEE.