The conventional frequency diverse array has range and angle coupled S-shaped spatial distribution. When transmitting and receiving operations are taken into account together, only energies in the target direction are concerned. To better support this condition, a transmit hybrid array
is proposed in this paper with a dotshaped beam pattern. The hybrid array is composed of a frequency diverse subarray (FDSA) and a phased subarray (PSA). If the frequency increment of FDSA is linearly increased, the beam pattern of the hybrid array exhibits a periodicity in the range dimension.
Moreover, if the frequency increment of FDSA is logarithmically increased, it yields a single maximum pointing at the target location with improved azimuthal resolution.
Existing power beam splitter has complex structure and is not easy to implement. The power beam splitters of 1×2 and 1×3 were designed based on two-dimensional square lattice photonic crystals. The beam splitters consist of a photonic crystal waveguide composed of gallium arsenide rods and tellurium dielectric rods defects. Defects are introduced into the self-collimated photonic crystal, and the material parameters are controlled by an applied electric field, thereby changing the beam splitting ratio and achieving tuned beam splitting. The efficiency of the 1×2 beam splitter designed by simulation analysis is the lowest, and the other efficiency is relatively high. It is confirmed that the light waves corresponding to 1200nm can be transmitted normally in the line defect, and the light waves of 1000 nm and 1400nm are only dispersed into these bandgaps. Since the propagation of light waves in these bandgaps causes energy loss, the beam splitting function cannot be achieved.
The traditional low delay transmission model of Internet of things has the problem of high packet loss rate, so a low delay transmission model of Internet of things based on data spectrum is designed. Firstly, the data preprocessing of the Internet of things mainly includes data fusion, data compression and data filtering, then the trust model is established, and finally the task transmission link model of the Internet of things is constructed to realize the low delay transmission of the Internet of things. The experimental results show that the low delay transmission model of IOT based on data spectrum has lower packet loss rate, higher network throughput and higher network resource utilization than the traditional model.
The early detection of cardiovascular diseases based on electrocardiogram (ECG) is very important for the timely treatment of cardiovascular patients, which increases the survival rate of patients. ECG is a visual representation that describes changes in cardiac bioelectricity and is
the basis for detecting heart health. With the rise of edge machine learning and Internet of Things (IoT) technologies, small machine learning models have received attention. This study proposes an ECG automatic classification method based on Internet of Things technology and LSTM network
to achieve early monitoring and early prevention of cardiovascular diseases. Specifically, this paper first proposes a single-layer bidirectional LSTM network structure. Make full use of the timing-dependent features of the sampling points before and after to automatically extract features.
The network structure is more lightweight and the calculation complexity is lower. In order to verify the effectiveness of the proposed classification model, the relevant comparison algorithm is used to verify on the MIT-BIH public data set. Secondly, the model is embedded in a wearable device
to automatically classify the collected ECG. Finally, when an abnormality is detected, the user is alerted by an alarm. The experimental results show that the proposed model has a simple structure and a high classification and recognition rate, which can meet the needs of wearable devices
for monitoring ECG of patients.
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