DeepSDR 101 是一款基于SDR软件无线电架构的DSP数字解调收音机,具有192kHz宽度的频谱图和瀑布图显示能力,配合16bit采样实现具有CW、AM、SSB、FM解调功能的高动态接收机。整机采用全铝合金CNC外壳,带有4.3寸800x480分辨率高亮IPS LCD 显示器的同时还保持了紧凑小巧的机身。 即刻带上它走到户外,享受自然风光和随时随地...
收听地点:安徽合肥收听机器:DeepSDR 101使用天线:70CM 拉杆天线收听时间:2022年07月23日 18:50-19:00(北京时间)9660kHz 中国之声广播, 视频播放量 1232、弹幕量 0、点赞数 3、投硬币枚数 0、收藏人数 5、转发人数 3, 视频作者 青雀bili, 作者简介 BH5HNU,相关视频:D
DeepSDR 101 是一款基于SDR软件无线电架构的DSP数字解调收音机,具有192kHz宽度的频谱图和瀑布图显示能力,配合16bit采样实现具有CW、AM、SSB和FM解调功能的高动态接收机。整机采用全铝合金CNC外壳,带有4.3寸800x480分辨率高亮IPS LCD 显示器的同时还保持了紧凑小巧的机身。 即刻带上它走到户外,享受自然风光和随时随地...
DeepSDR 101 is a DSP digital demodulation radio based on SDR software-defined radio architecture. It has a 192kHz width spectrogram and waterfall display capabilities, and cooperates with 16bit sampling to realize a high dynamic receiver with CW, AM, SSB, FM demodulation functions. The whole mac...
In terms of those SI4732 receivers, the newer, slim-line, ATS100 mini-SDR appears to be the most comparable radio to the DeepSDR 101, which is under review here. Therefore, I was curious and took note when I heard that Deepelec is also now manufacturing a newer version of a Software...
It mainly includes two strategies, global residual learning (GRL) and local residual learning (LRL) (Sdraka et al., 2022). GRL is employed to learn the residual between the input and output images to recover the high-frequency details, while LRL represents a local shortcut inserted between ...
先进的频率扫描: 这款DeepVNA 101天线分析仪涵盖10K-1.5GHz的宽频率范围,使其成为各种应用的理想工具,包括天线、滤波器和其他射频组件的测试和优化。 高分辨率显示器: 配备4.3 “屏幕,该分析仪可提供清晰,详细的测量结果视觉表示,使用户可以轻松解释和分析数据。
精确的频率测量: V3.2 DeepVNA 101矢量网络分析仪涵盖10kHz至1.5GHz的宽频率范围,可精确测量各种RF信号。 高级显示: 该设备具有4.3英寸屏幕,可清晰显示测量数据,确保读数准确且易于解释。 持久的电池寿命: 电池容量为5000mah/3.7V,该设备可以长时间运行而无需充电,非常适合现场测量。
D., Sdrolias, M., Gaina, C. & Roest, W. R. Age, spreading rates, and spreading asymmetry of the world’s ocean crust. Geochem. Geophys. Geosyst. 9, Q04006 (2008). Article Google Scholar Bonatti, E. et al. Steady-state creation of crust-free lithosphere at cold spots in mid-...
SDR utilizes the dominant eigenvalue α of the system topology to achieve accurate dimension reduction grounded in a theoretical premise. These two approaches are exemplary methods for estimating resilience of networked systems from the analytical perspective. The experiment results demonstrate ResInf ...