No abstract

In this paper, we propose a unified deep learning model for monitoring elderly in execution of daily life activities such as eating, sleeping or taking medication. The proposed approach consists of three stages which are activity recognition, anomaly detection and next activity prediction. Such a system can provide useful information for the elderly, caregivers and medical teams to identify activities and generate preventive and corrective measures. In literature, these stages are discussed separately, however, in our approach, we make use of each stage to progress into the next stage. At first, activity recognition based on different extracted features is performed using a deep neural network (DNN), then an overcomplete-deep autoencoder (OCD-AE) is employed to separate the normal from anomalous activities. Finally, a cleaned sequence of consecutive activities is constructed and used by a long short-term memory (LSTM) algorithm to predict the next activity. Since the last two stages depend on the activity recognition stage, we propose to increase its accuracy by exploiting different extracted features. The performance of the proposed unified approach has been evaluated on real smart home datasets to demonstrate its ability to recognize activities, detect anomalies and predict the next activity.

No abstract

No abstract

In this paper, a new precoder for a coherent optical filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) system is proposed. The precoder is designed based on an iterative polynomial eigenvalue decomposition (PEVD) algorithm to jointly mitigate the inter-symbol interference and inter-carrier interference. The PEVD algorithm is used to decompose a polynomial channel matrix into polynomial eigenvectors and eigenvalues matrices, then a precoder is designed based on the decomposed matrices. The precoder acts as a filter applied to each subcarrier and to its adjacent subcarriers. In addition, a new adaptive optimum energy algorithm is proposed to truncate the insignificant precoder filter coefficients produced by the PEVD algorithm and consequently reduce the computational complexity. A mathematical model and algorithm for implementing the precoder are also presented. Robustness of the proposed precoder has been analyzed and compared to existing precoder in optical channel with different dispersion effects. Numerical results demonstrate that the new precoder significantly outperforms the existing precoder in terms of error vector magnitude, bit error rate, Frobenius norm of the error matrix, and computational complexity.