Defense Advanced Research Projects AgencyTagged Content List

Algorithms

A process or rule set used for calculations or other problem-solving operations

Showing 65 results for Algorithms RSS
Conventional analog-to-digital converters (ADCs) are fundamentally limited by timing jitter in the sampling source, forcing a trade-off between bandwidth and resolution. As a result, radio frequency (RF) systems are typically designed with narrow-bandwidth channels. These engineering constraints present problems when faced with broadband signals and ultra-short pulses. At high carrier frequencies, RF systems are further limited by the tuner that must mix down to baseband for electronic digitization.
Machine learning has shown remarkable success across many application areas in recent years, leveraging advances in computing power and the availability of large sets of training data. It provides a tremendous opportunity to deploy data-driven systems in more complex and interactive tasks including personalized autonomy, agile robotics, self-driving vehicles, and smart cities. Despite dramatic progress, the machine learning community still lacks an understanding of the trade-offs and mathematical limitations of related technologies for a given domain, problem, or dataset.
FunCC aims to uncover fundamental principles of resilient self-organized complex systems applicable to domains spanning autonomous systems to biological networks, the immune system, and ecosystems. The dynamics and evolution of complex collectives are explored using new frameworks that embrace agent heterogeneity, stochasticity, distributed control, and diffusion of (mis)information.
In supervised machine learning (ML), the ML system learns by example to recognize things, such as objects in images or speech. Humans provide these examples to ML systems during their training in the form of labeled data. With enough labeled data, we can generally build accurate pattern recognition models.
| AI | Algorithms | Data |
LADS will develop a new protection paradigm that separates security-monitoring functionality from the protected system, focusing on low-resource, embedded and Internet of Things (IoT) devices. The program will explore technologies to associate the running state of a device with its involuntary analog emissions across different physical modalities including, but not limited to, electromagnetic emissions, acoustic emanations, power fluctuations and thermal output variations.