What We Do
It helps to be very flexible in picking up the most interesting information out of the noisy real-world signals.
We use DSP techniques almost daily, taking them as a necessary part of all the measurement instruments, data compression applications, and artificial intelligence (AI).
Technologies and Tools
We use MATLAB, Scilab, Octave, Python, and Delphi, among others.
Another part is IDEs for the implementation of algorithms into the firmware. These tools come from world leaders in firmware creation support and well-known chip producers, e.g., Microsoft Visual Studio Code and TI Code Composer Studio, where mostly C/C++ programming languages find their efficient usage.
Our outputs are used mainly in measurement instruments, radiocommunication, the Internet of Things (IoT), and the medical industry.
Our Typical Workflow
We come from the system architecture suggestion and define requirements on the signal processing components at first. We simulate the individual components and optimize their performance.
Then, we implement the components in proper programming languages and debug them at the target platform. The next step is the integration with the rest of the system.
Our work includes: Architecture ― Simulation ― Implementation ― Deployment ― Verification.
We recommend (of course) making good system testing and measurement at the end of work. The test reports are drafted in the last stage.
We developed a few spectrum analyzers, vector signal generators, and arbitrary generators at that time. Later, we continued with VHF and UHF receivers and transmitters. Unsurprisingly, these also need signal processing to achieve proper dynamic range and signal purity.
In recent years, we have shifted our focus to compact measurement instruments.
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