Stochastic signals processing

    Our portfolio of skills and experiences is not exclusively audio-oriented.  We have done a lot of work in the highly specialized area of signal processing of stochastic (random) signals and energy distribution. A good example of such signals is partial discharges in high voltage isolation systems and ionizing radiation signals from detectors based on scintillation, semiconductor and gas filled ion chamber principles.

    Traditional analytical systems for the processing of such signals are very expensive, complex and not easily customizable. With the FPGA technology and our experience in digital signal processing technologies we were able to achieve overall system simplification with high degree of customization.  The processing chain still remains combined type, consisting of all three processing domains: Analogue, embedded digital and purely software based. 

    Tasks and technology areas usually involved in stochastic signal processing:

  • Analogue  front end electronics

  • Signal acquisition

  • Noise shaping and cancellation filters

  • Signal shaping, filtering and base line restoring

  • Non-linear re-scaling

  • Data pre-processing and sorting algorithms

  • Data structuring and local storage

  • Data transportation and evaluation

  • Data and results visualization and process control

    Most of the tasks listed above can be done digitally in an FPGA to avoid additional processing delay and uncertainty when done in the analogue domain. For instance, signal shaping like trapezoidal pulse filters are difficult to implement in the analogue world accurately. Raw data storage is useful for off-line processing, but continuously working systems require to process data on-line and transmit only processing results or selected signal parameters. Another specialty of ours is hardware-accelerated range compression; non-linear range scaling with balanced compression and data resolution trade-off.

     Our designs are used in research, quality control and assurance, monitoring networks and in other highly demanding fields.