Signal Data Analysis
Unlock insights from a variety of signal-based sources.
Different types of signals
Our expertise covers various types of signals, including audio, image, video, sensor data (medical, motion…), time series and more. Whether you're dealing with biometric signals, communication signals, or industrial sensor data, our team has the skills to process, analyze, and derive meaningful insights from these diverse sources.
Signal Analysis Technologies
Our tools and techniques enable us to process raw signal data and convert it into usable formats. We employ advanced methods such as Fourier Transform, wavelet analysis, and machine learning algorithms to identify patterns, trends, and anomalies within the signals. These technologies allow us to uncover hidden information and provide actionable insights for a wide range of applications, from medical diagnostics to industrial monitoring.
Signal Segmentation
It involves dividing continuous signals into distinct segments based on specific characteristics like spacial or time-based patterns. For example, in ECG analysis, signal segmentation can detect distinct phases like systole and diastole, allowing detailed examination of cardiac cycles. Our signal segmentation solutions can adapt to various signal types, ensuring that each segment represents a meaningful event or period within the data. This approach provides a clearer understanding of signal structure and aids in subsequent analysis and feature extraction.
Signal Classification
Our classification models are trained to recognize different patterns and characteristics within the signal segments. This approach allows us to automatically classify signals based on specific criteria, streamlining data organization and analysis. Whether you're classifying audio signals for speech recognition or image signals for object detection, our signal classification solutions deliver accuracy and efficiency.
