FPGA Design & Development
We use our signal processing expertise to build industrial and defense applications
In many applications both Signal processing techniques and Machine/Deep learning methods are used together to build effective solutions. Although Machine learning and Deep learning methods are effective in many applications they still require huge datasets to train the model which is not the case with Signal processing techniques. Many times, the noise intensity levels are so high that its not possible to apply any ML/DL methods until pre-processed using signal processing techniques.
We have extensive experience in 1D, 2D, motion amplification technology, extracting signal from low S/N environments. We have built our own Wavelet IP libraries for FPGA.
Key Highlights
- Inferring & Separating Signal from Noise
- Analysis in time domain and frequency domain
- Joint time-frequency analysis
Applications
- Radar Processing
- Sound and Speech Processing
- Digital Communications
- Image Processing
Platforms
- Linux Based Embedded Systems
- x86
- FPGA
Advanced Signal Processing
We have extensive experience in 1D, 2D, motion amplification technology, extracting signal from low S/N environments. We have built our own Wavelet IP libraries for FPGA.
Key Highlights
- Inferring & Separating Signal from Noise
- Analysis in time domain and frequency domain
- Joint time-frequency analysis
Applications
- Radar Processing
- Sound and Speech Processing
- Digital Communications
- Image Processing
Platforms
- Linux Based Embedded Systems
- x86
- FPGA
Ready to Integrate YV Modules
We accelerate speed to market by using our existing ready to integrate modules that have gone through regressive testing over a period of time.
Signal Processing
Wavelet Libraries
FPGA Implementation
Video & Image Processing
