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RSCW demonstrates a Linux/Unix command-line utility engineered for **Morse code** decoding via a computer's sound card. It specifically targets the extraction of weak CW signals from noise, operating on 8-bit, 8000 samples/second audio input, typically from `/dev/dsp`. The program outputs decoded characters to `stdout`, supporting user-specified speeds in words per minute (WPM) and carrier frequencies. While effective for machine-sent signals, it exhibits a 2-second decoding lag and requires manual speed input, making it less suitable for general-purpose, real-time contest operation. The resource details the program's components, including `rscw` (the main decoder), `rscwx` (an X11 graphical auxiliary for spectrum and internal signal visualization), `rs12tlmdec` (a specialized decoder for RS-12 amateur radio satellite telemetry), and `noisycw` (a utility for generating noisy Morse signals for testing). Installation instructions involve downloading a `.tgz` file, compiling with `Make`, and requiring the FFTW library (and GTK 2.0 for `rscwx`). Performance is illustrated with a .wav file example of a 12 WPM, 800 Hz CW signal at 12 dB Eb/N0, showcasing RSCW's near-error-free decoding of a test message. The site provides command-line examples utilizing `sox` for audio conversion and `noisycw` for signal generation, inviting comparisons with other decoding software and human operators, particularly for weak signal conditions.

In his page the author includes 27 mp3 audio files that compose the whole CW training course, instructions and whole lessons transcript are available in Italian and English.

Monitoring extremely weak signals in the QRSS (Very Slow Morse) mode requires specialized receiving and processing capabilities to extract information below the typical noise floor. This project provides a software solution, _QrssPiG_, designed to run on a Raspberry Pi, enabling it to function as a dedicated QRSS grabber. It interfaces with various Software Defined Radio (SDR) devices, including the popular _rtl-sdr_ dongles and _HackRF_ units, to acquire raw I/Q data streams. The software then performs the necessary signal processing to visualize and decode these faint, long-duration CW transmissions, often operating with milliwatts of power. The system leverages the computational power of the Raspberry Pi for real-time signal analysis, allowing hams to participate in QRSS experiments and monitor distant beacons. It supports different SDR hardware, offering flexibility in setup and deployment for home stations or remote monitoring sites. The project includes detailed instructions for installation and configuration, making it accessible for those familiar with Linux environments. This grabber is particularly useful for tracking propagation on the LF and HF bands where QRSS activity is common, providing a visual representation of signal presence over extended periods.

The Code Practice Oscillator kit, featured at TechFest 2020, provides a straightforward device for Morse Code skill development. It utilizes two 3V coin batteries for power and is designed for ease of construction, making it accessible for hams of various ages. The kit's primary technical substance revolves around generating an audible tone for practicing Morse Code timing and ear training, with a downloadable schematic detailing its electronic configuration. Construction of the oscillator involves soldering, with adult supervision recommended for younger builders. The kit's practical application lies in offering a hands-on method for beginners to learn Morse Code and for experienced operators to refine their sending abilities. Instructions for assembly are available as a downloadable PDF, complementing the schematic to guide users through the building process.

This page presents a project involving attaching an amateur radio transceiver to an Arduino to create a 'fox' signal for radio direction finding practice. This project can be used to practice direction finding skills by locating a radio transmitter in a hidden location. The project involves transmitting the station ID using Morse code and can be a fun and educational activity for students or hobbyists interested in radio direction finding. The author shares their experience with radio direction finding and provides instructions on how to build the project using a Baofeng UV-3R radio and an Arduino Uno.