Zohreh Mohammadkhani

This Fetal electrocardiogram is a standard method to identify and diagnose fetal diseases. Therefore, effective techniques are needed to monitor fetal conditions during pregnancy and delivery. Meanwhile, obtaining the fetal electrocardiogram (FECG) signal, which contains the electrical activity of the fetal heart, has great importance, Of course, this signal is contaminated with many noises and disturbances and the most important of them is the mother's electrocardiogram signal. Inherently, the NI-ECG signal contains the maternal ECG signal, which has a larger amplitude than the fetal ECG signal. Therefore, it is not easy to detect the fetal QRS complex in order to control the condition of the fetus and prevent congenital defects. According to the above explanations, in this article, a deep learning approach based on a convolutional neural network is proposed to separate the electrocardiogram signals of the mother from the fetus without separating the mother's ECG signal. The proposed algorithm is able to reliably detect the fetal QRS complex. Also, in addition to not needing feature extraction steps, it has been able to show more suitable performance than the best methods proposed in previous research in terms of detection accuracy

Wireless technology, one of the fastest segments of the modern communications industry is growing. The IEEE 802.16e standard as we know by the name mobile Worldwide Interoperability for Microwave Access (WiMAX) commonly, the latest wireless technology is broadband wireless access for over long distances. Orthogonal Frequency Division Multiplexing (OFDM) concept to speed up data transfer and to reduce adverse effects such as interference with the internal display (ISI) and the Input Channel Interference (ICI) is used in OFDM. For next generation air wireless broadband systems play an interface role. In this review article, we study a method based on a finite state machine (FSM) for modeling multimode addressable generator WiMAX interleaver using Very High speed integrated Circuit Hardware Description Language (VHDL) on Field Programmable Gate Array (FPGA) with multi-rate codes and programs for all standard IEEE 802.16e, has been introduced. The proposed method works better at high frequencies, and with minimal loss of logic cells compared with the existing FPGA-based approach, uses flip-flops. In the end, interleaver in the WiMAX system and modeling of the hardware was studied.