Cancelable ECG Biometrics Using Compressive Sensing-Generalized Likelihood Ratio Test

On ECG reconstruction using weighted-compressive sensing.

The potential of the new weighted-compressive sensing approach for efficient reconstruction of electrocardiograph (ECG) signals is investigated. This is motivated by the observation that ECG signals are hugely sparse in the frequency domain and the sparsity changes slowly over time. The underlying idea of this approach is to extract an estimated probability model for the signal of interest, and...

Generalized Likelihood Ratio Test for Selecting

A generalized likelihood ratio test is considered for testing acoustic propagation models in the context of environmental parameter inversion. In the following, we use the term \hierarchy of models" to denote a sequence of model structures M1;M2;... in which each particular model structure Mn contains all previous ones as special cases. We propose a combined parameter estimation and multiple se...

Generalized Distributed Compressive Sensing

Distributed Compressive Sensing (DCS) [1] improves the signal recovery performance of multi signal ensembles by exploiting both intraand inter-signal correlation and sparsity structure. However, the existing DCS was proposed for a very limited ensemble of signals that has single common information [1]. In this paper, we propose a generalized DCS (GDCS) which can improve sparse signal detection ...

Cancelable Biometrics for Bimodal Cryptosystems

Biometric-based techniques have recently emerged as a trustworthy and effective approach of user authentication; however, unlike conventional authentication methods such as passwords and tokens, if an enrolled biometric template is compromised, usually it cannot be revoked or re-issued. In this paper, four naive cancelable techniques, namely, shifting, password-dependent shifting, XOR and addin...

Generalized Likelihood Ratio Statistics