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Nowadays identification systems is being used in applications where security is required. However, the authentication with one layer of protection is obsolete. This fact causes that new threatens have appeared and that the number of attempts to break different systems has increased. In this paper, we propose a multifactor authentication system. During the authentication process, several validation factors may be needed to verify the user's identity. The goal is to perform an integrated application by layers such as biometrics and radio frequency identification (RFID). Based on this concept, the proposed method has an authentication engine with two independent credentials where an instrumentation system with an infrared LED and photodiode has been developed to evaluate fake fingerprints.

In this paper, we address a new approach for high-resolution reconstruction and enhancement of remote sensing (RS) imagery in near-real computational time based on the aggregated hardware/software (HW/SW) co-design paradigm. The software design is aimed at the algorithmic-level decrease of the computational load of the large-scale RS image enhancement tasks via incorporating into the fixed-point iterative reconstruction/enhancement procedures the convex convergence enforcement regularization by constructing the proper projectors onto convex sets (POCS) in the solution domain. The established POCS-regularized iterative techniques are performed separately along the range and azimuth directions over the RS scene frame making an optimal use of the sparseness properties of the employed sensor system modulation format. The hardware design is oriented on employing the Xilinx Field Programmable Gate Array XC4VSX35-10ff668 and performing the image enhancement/reconstruction tasks in a computationally efficient parallel fashion that meets the near-real time imaging system requirements. Finally, we report some simulation results and discuss the implementation performance issues related to enhancement of the real-world RS imagery indicative of the significantly increased performance efficiency gained with the developed approach.

This paper presents a system for recognition of voiced segments in Spanish esophageal speech. It exposes different algorithms for the feature extraction of speech segment like formant analysis, linear prediction coefficients (LPC) and Mel Frequency Cepstral Coefficients (MFCC), as well as, the recognition stage through the Hidden Markov Models. Simulation results are presented for normal and esophageal speech. The system was implemented in a real time processing platform based on a digital signal processor TMS320C5416 of Texas Instruments.

In this paper we develop a blind adaptive multiuser detector for muticarrier (MC) codedivision multiple access (CDMA) based on constant modulus algorithm (CMA). The proposed system results in a modification of a blind multicarrier CDMA receiver proposed before. We introduce a dedsion- feedback blind adaptive multiuser detector structure at the end of the receiver, which is adapted without knowing of system parameters such as the channel or transmitted signal. Simulations indicate that the performance of the DFBD is acceptable while conserve a reasonable computational cast. I. INTRODUCTION As the radio fiequency spectrum is a scarce resource, future wireless radio networks need to make efficient use of the frequency spectrum by providing high capacity in terms of the number of users allowed in the system. As a consequence, modulation and multiple access techniques designed specifically for wireless channels play an important role in achieving this goal. For mobile communication systems, diversity reception is essential to counteract the effects of fading radio channels. Direct-sequence (DS) code division multiple access (CDMA) is a multiplexing technique where several independent users share a common channel by modulating preassigned signature waveforms. The receiver then observes the sum of the transmitted signals over an additive white Gaussian noise (AWGN) channel. The major limitation on the performance and channel capacity of DS-CDMA system is the multiple-access interference (MAI) due to simultaneous transmissions. The conventional matched filter (MF) detector cannot suppress MA1 efectively, and it suffers from the near-far problem. Since CDMA is not fundamentally MAI limited, multiuser detection (MUD) techniques can substantially improve the performance of a CDMA system. While the optima1 multiuser detector, which is essentially a maximum-likelihood (ML) sequence detector, has prohibitive complexity, many other multiuser detectors with relatively low complexity such as decision feedback detector, successive or parallel interference canceller, and linear multiuser detectors have been developed. The linear decorrelator removes all cross-correlations between active users and thereby eliminates MA1 at the price of enhancing noise (2).

The interest in developing a robust on-line signature verification system has greatly increased. Three kinds of forgeries, random forgery, simple forgery and expert forgery, must be considered. Dynamic features extraction for an on-line signature verification system is presented. The dynamic features are extracted from authentic and forged signatures with relatively low computational cost. All kind of forgeries, included expert forgeries, are considered for detection as forged signatures. Computer simulation results show a desirable performance of the proposed system.