Francisco M. de Assis

QUANTUM ZERO-ERROR CAPACITY

We define a new kind of quantum channel capacity by extending the concept of zero-error capacity for a noisy quantum channel. The necessary requirement for which a quantum channel has zero-error capacity greater than zero is given. Finally, we point out some directions on how to calculate the zero-error capacity of such channels.

A comparative study of use of shannon, rényi and tsallis entropy for attribute selecting in network intrusion detection

The selection of optimal attributes from the set of all possible attributes of a network traffic is the first step to detect network intrusions. However, in order to optimize the effectiveness of intrusion detection procedure and decrease its complexity, it is still a challenge to select an optimal attribute subset. In this context, the primary problem of attribute selection is the criterion to evaluate a given attribute subset. In this work, it is presented an evaluation of Rényi and Tsallis entropy performances compared with Shannon entropy in order to obtain an optimal attribute subset that increase the capability of the Intrusion Detection System to classify the traffic as normal or as suspicious. In the experimental results, the detection accuracy and the false alarm rate almost remains the same or even becomes better depending on the attack category (e.g. in the DoS and Probing attack) when small attribute subsets are used compared when all attributes are used.

Analysis and optimization of wavelet-coded communication systems

Since its advent, wavelet coding has been recognized as a promising technique for wireless transmission systems, especially due to its low decoding complexity and good performance over multipath fading. However, this technique requires unusual modulation schemes in order to be fully exploited. A BER analysis of wavelet-coded transmission systems over Rayleigh fading channels is presented in this work. This analysis is used in the design of novel signal constellations for wavelet-coded systems by means of numerical performance optimization. Numerical results obtained from analysis and simulations show that the wavelet-coded systems derived herein have very good performance characteristics over fading channels.

A comparative study of use of Shannon, Rényi and Tsallis entropy for attribute selecting in network intrusion detection

The selection of optimal attributes from the set of all possible attributes of a network traffic is the first step to detect network intrusions. However, in order to optimize the effectiveness of intrusion detection procedure and decrease its complexity, it is still a challenge to select an optimal attribute subset. In this context, the primary problem of attribute selection is the criterion to evaluate a given attribute subset. In this work, it is presented an evaluation of Renyi and Tsallis entropy performances compared with Shannon entropy in order to obtain an optimal attribute subset that increase the capability of the Intrusion Detection System to classify the traffic as normal or as suspicious. In the experimental results, the detection accuracy and the false alarm rate almost remains the same or even becomes better depending on the attack category (e.g. in the DoS and Probing attack) when small attribute subsets are used compared when all attributes are used.

Decision Tree Based on Shannon, Rényi and Tsallis Entropies for Intrusion Tolerant Systems

This paper describes a comparative study of the use of Shannon, Renyi and Tsallis entropies for designing Decision Tree, with goal to find more efficient alternatives applied to Intrusion Tolerant Systems. Decision Tree has been used in classification model problems related to intrusion detection in networks, presenting good results. A very used decision tree is the C4.5 one that applies the Shannon entropy in order to choose the attributes that better divide data intoclasses. However, other ways to measure entropy, e.g., Tsallis and Renyi entropy, may be applied aiming at guaranteeing better generalization related to split criteria. Experimental results demonstrate that Tsallis and Renyi entropy can be used to construct more compact and efficient decision trees compared with Shannon entropy and these models can to provide more accurate intrusion tolerante systems.

Evaluation of Alzheimer's disease by analysis of MR images using Objective Dialectical Classifiers as an alternative to ADC maps

Alzheimers disease is the most common cause of dementia, yet hard to diagnose precisely without invasive techniques, particularly at the onset of the disease. This work approaches image analysis and classification of synthetic multispectral images composed by diffusion-weighted (DW) magnetic resonance (MR) cerebral images for the evaluation of cerebrospinal fluid area and measuring the advance of Alzheimers disease. A clinical 1.5 T MR imaging system was used to acquire all images presented. The classification methods are based on Objective Dialectical Classifiers, a new method based on Dialectics as defined in the Philosophy of Praxis. A 2-degree polynomial network with supervised training is used to generate the ground truth image. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map.

Zero-Error Capacity of a Quantum Channel

We define the quantum zero-error capacity, a new kind of classical capacity of a noisy quantum channel. Moreover, the necessary requirement for which a quantum channel has zero-error capacity greater than zero is also given.

Performance of a PSK system with wavelet time diversity over flat Rayleigh fading channels

This paper presents a novel system for transmission over wireless channels. This system combines a smart interleaving that uses a Wavelet Coefficient Matrix (WCM) with a time diversity scheme. It is shown by computational simulation that the proposed system presents a good performance over channels with memory characterized by the flat Rayleigh fading.

Mixed Test Pattern Generation Using a Single Parallel LFSR

In this paper, new method is described to design a mixed-mode test pattern generator based only on a simple and single linear feedback shift register (LFSR). Such an LFSR synthesized by the Berlekamp-Massey algorithm is obtained in order to generate pre-computed deterministic test patterns to detect the hard-to-detect faults of the circuit. Among them, residual test patterns are generated to detect the others. Using the proposed method, a circuit can be tested at-speed and complete fault coverage is achieved with a small number of test patterns and small area overhead. The experimental results show that the proposed method compares favorably to other previous methods

Soft-decision demodulation of wavelet-coded PSK signals over flat rayleigh fading channels

This paper proposes a new soft-decision approach for demodulating wavelet-coded PSK signals, which is based on minimizing a mean squared error. Performance evaluation and comparison with the usual hard-decision demodulated wavelet- coded schemes are performed via computer simulation. The numerical results so obtained indicate that the proposed technique is an effective tool for performance improvement of wavelet-coded PSK systems. Therefore, this new approach for soft-decision may lead to new alternatives for exploiting the potential of wavelet coding for digital communications over wireless channels.