An increase in the accuracy of identification of Activities of Daily Living (ADL) is very important for different goals of Enhanced Living Environments and for Ambient Assisted Living (AAL) tasks. This increase may be achieved through identification of the surrounding environment. Although this is usually used to identify the location, ADL recognition can be improved with the identification of the sound in that particular environment. This paper reviews audio fingerprinting techniques that can be used with the acoustic data acquired from mobile devices. A comprehensive literature search was conducted in order to identify relevant English language works aimed at the identification of the environment of ADLs using data acquired with mobile devices, published between 2002 and 2017. In total, 40 studies were analyzed and selected from 115 citations. The results highlight several audio fingerprinting techniques, including Modified discrete cosine transform (MDCT), Mel-frequency cepstrum coefficients (MFCC), Principal Component Analysis (PCA), Fast Fourier Transform (FFT), Gaussian mixture models (GMM), likelihood estimation, logarithmic moduled complex lapped transform (LMCLT), support vector machine (SVM), constant Q transform (CQT), symmetric pairwise boosting (SPB), Philips robust hash (PRH), linear discriminant analysis (LDA) and discrete cosine transform (DCT).
This article presents a measurement strategy and a characterization bench for the evaluation of Signal to Noise and Distortion Ratio (SNDR) in nonlinear wireless systems when in presence of memory effects. This measurement proposal will be combined with a closed analysis of the nonlinear mechanisms appearing in communication systems presenting memory. The analysis of this memory mechanism, when the system is excited by complex modulated signals with different statistics, will be a useful tool for design engineers to evaluate the degradation of SNDR in nonlinear wireless systems. Finally, the proposed measurement approach will be applied to a CDMA communication system, by evaluating carefully the SNDR of that system.
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