Radar Signal Modulation Recognition Based on Sep-ResNet

With the development of signal processing technology and the use of new radar systems, signal aliasing and electronic interference have occurred in space. The electromagnetic signals have become extremely complicated in their current applications in space, causing difficult problems in terms of accurately identifying radar-modulated signals in low signal-to-noise ratio (SNR) environments. To address this problem, in this paper, we propose an intelligent recognition method that combines time–frequency (T–F) analysis and a deep neural network to identify radar modulation signals. The T–F analysis of the complex Morlet wavelet transform (CMWT) method is used to extract the characteristics of signals and obtain the T–F images. Adaptive filtering and morphological processing are used in T–F image enhancement to reduce the interference of noise on signal characteristics. A deep neural network with the channel-separable ResNet (Sep-ResNet) is used to classify enhanced T–F images. The proposed method completes high-accuracy intelligent recognition of radar-modulated signals in a low-SNR environment. When the SNR is −10 dB, the probability of successful recognition (PSR) is 93.44%.

M-ary quadrature amplitude modulation order optimization for terahertz wireless communications over dispersive channels

Highly accurate atmospheric models, based on molecular resonance information contained within the HITRAN database, were used to simulate the propagation of high capacity single-carrier quadrature amplitude modulated signals through the atmosphere for various modulation orders. For high-bandwidth signals such as those considered in this work, group velocity dispersion caused by atmospheric gases distorts the modulated waveform, which may produce bit errors. This leads to stricter Signal-To-Noise Ratio requirements for error-free operation, and this effect is more pronounced in high-order modulation schemes. At the same time, high-order modulation schemes are more spectrally efficient, which reduces the bandwidth required to maintain a given data rate, and thus reduces the total group velocity dispersion in the link, resulting in less distortion and better performance. Our work with M-ary quadrature amplitude modulated signals shows that optimal selection of modulation order can minimize these conflicting effects, resulting in decreased error rate, and reducing the performance requirements placed on any equalizers, other dispersion-compensating technologies, or signal processing hardware.

Effect of Modulated Signals on Vibrational Resonance in a Harmonically Trapped Potential System

We consider a harmonically trapped potential system driven by modulated signals with two widely different frequencies ω and Ω, where Ω >> ω. The forms of modulated signals are amplitude modulated (AM) and frequency-modulated (FM) signals. An amplitude-modulated external signal is consisting of a low-frequency (ω) component and two high-frequencies (Ω + ω) and (Ω − ω) whereas the frequency modulated signal consisting of the frequency components such as f sinωt cos(g cosΩt) and f sin(g cosΩt) cosωt. Depending upon the values of the parameters in the potential function, an odd number of potential wells of different depths can be generated. We numerically investigate the effect of these modulated signals on vibrational resonance (VR) in single-well, three-well, five-well and seven-well potentials. Different from traditional VR theory in the present paper, the enhancement of VR is made by the amplitudes of the AM and FM signals. We show the enhanced response amplitude (Q) at the low-frequency ω, showing the greater number of resonance peaks and non-decay response amplitude on the response amplitude curve due to the modulated signals in all the potential wells. Furthermore, the response amplitude of the system driven by the AM signal exhibits hysteresis and a jump phenomenon. Such behavior of Q is not observed in the system driven by the FM signal.

Anticipatory 50-kHz Precontact Ultrasonic Vocalizations and Sexual Motivation: Characteristic Pattern of Ultrasound Subtypes in an Individual Analyzed Profile

We verified the hypothesis of the existence of forms of individual-specific differences in the emission of anticipatory precontact vocalization (PVs) indicating individualization related to sexual experience and motivation in male rats. Long-Evans males were individually placed in a chamber and 50-kHz ultrasounds were recorded during 5-min periods. In experiment 1, PVs were recorded before the introduction of a female in four consecutive sessions during the acquisition of sexual experience. In experiment 2, PVs were analyzed in three groups of sexually experienced males: with the highest, moderate, and the lowest sexual motivation based on previous copulatory activity. In both experiments, the total number of ultrasounds, as well as 14 different specific subtypes, was measured. The ultrasound profiles for each male were created by analyzing the proportions of specific dominant subtypes of so-called 50-kHz calls. We decided that the dominant ultrasounds were those that represented more than 10% of the total recorded signals in a particular session. The number of PVs was positively correlated with the acquisition of sexual experience and previous copulatory efficiency (measured as the number of sessions with ejaculation). Furthermore, PVs showed domination of the frequency modulated signals (complex and composite) as well as flat and short with upward ramp ultrasounds with some individual differences, regardless of the level of sexual motivation. The results show a characteristic pattern of PVs and confirm the hypothesis that the number of PVs is a parameter reflecting the level of sexual motivation.