The signal analysis solutions team has years of experience applying expert data analysis to a wide variety of problems. They have experience implementing machine learning techniques such as SVM, RVM, and random forests to analyze data from multiple sensors and applications, including biomedical applications analyzing EEG and industrial applications analyzing ground penetrating radar, camera images, and ultrasound traces. They are knowlegeable about proper cross-validation techniques to ensure robust and repeatable performance across multiple data collections.

While machine learning toolboxes are often available for free download, achieving customer goals often requires more than just plugging data into these algorithms. Deeper understanding of the strengths and weaknesses of these algorithms can improve results and ensure repeatable success. Performance with these algorithms can often be improved with various data pre-processing techniques and extraction of informative characteristics of the data. The signal analysis team can custom-design algorithms that take data straight from the sensor and handle all of the processing to output. The customer's specific costs and needs are incorporated into the algorithm development to optimize the most crucial aspects of analysis.

Improper data collection can result in misleading algorithm successes that often aren't replicable with new data collections. The signal analysis solutions team can provide advice on collecting data with a focus on achieving customer goals and developing robust data analytics algorithms. They can also custom design user interfaces that controls data collection and allows the customer to apply data analysis techniques in-house.