WebFME Connectors. Amphenol RF’s FME connectors are a miniature 50 ohm series offering performance from DC to 200 MHz. This connector series is used for mobile antenna applications adapted for UHF, Mini UHF, TNC, BNC and N-Type connector interfaces using between-series adapters. It is primarily used with RG-58 coaxial cables. Features and … WebQuando se trata de conectores elétricos, existem muitos tipos diferentes disponíveis no mercado. Dois tipos populares são os conectores GX12 e GX16.
SMA Plug (Male) Jack (Female) RF Adapters - In Series – Mouser
WebOct 14, 2024 · Posted by Michael Crudele on October 14, 2024. Over the years, we've had many customers come to us looking to clarify RF connector types when they are specifying and purchasing RF coaxial cable assemblies. There are many different types of connectors out there, including Type-N, UHF (aka PL-259 / SO-239) TNC, RPTNC, BNC, SMA & … WebThese FME to SMA adapters operate at frequencies as high as 2 GHz. FME to SMA adapters from Pasternack are available in male / plug and female / jack, straight … graph algorithm platform benchmark suite
FME Cables & Adapters for Antennas - Data Alliance
WebElectrical specifications of the N-type connector. Frequency range: Type N connectors have a frequency range of DC to 11 GHz. Impedance: 50 Ohms or 75 Ohms (there is a slight structural difference between the 50 Ohm and 75 Ohm versions). Voltage rating: The peak voltage of the contemporary N-type connector is 1500 volts. FME (For Mobile Equipment) is a miniature 50Ω RF connector series offering excellent performance from DC to 2000 MHz (Note: 2.4GHz for Amphenol 81-169) used primarily with RG-58 or equivalent coaxial cables employed in mobile applications and installations. The FME female is designed to be low diameter to allow cables it has been inst… WebFME/F-Type/N-Type. BNC. RCA. Multi-pin. Toslink. XLR/Speakon Connectors. Power Connectors. Multi Pin. Crimp Lugs & Terminals. High Current & Anderson. Quick Connect. DC Power. Banana/Binding Posts. … graph algorithms complexity