Sentence examples for signal processing network from inspiring English sources
It is based on the idea of abstract signal sources and signal sinks that are connected to a signal processing network.
Office: 301 194 Nassau St. Research Area: High-dimensional estimation, machine learning, convex and nonconvex optimization, information theory, statistics, statistical signal processing, network science, and their applications in medical imaging and computational biology.
His research interests include high-dimensional estimation, machine learning, convex and nonconvex optimization, information theory, statistics, statistical signal processing, network science, and their applications in medical imaging and computational biology.
Advances in methods for signal processing, network analysis, dimensionality reduction, and optimal control — developed in lockstep with advances in experimental neurotechnology — promise major breakthroughs in multiple fundamental neuroscience problems.
Networking Neurons: Making Super Synapses — Volunteers from the Undergraduate Program in Neuroscience will explain how brain cells called neurons connect to one another, forming a signal processing network.
It is interesting to know that Hartley-Hilbert and Fourier-Hilbert transforms enjoy wide applications in signal processing, network theory and some other geophysical applications.
Filtering and design of suitable filters are the basic requirement in most of modern signal processing networks.
We have recently introduced an approach to constructing complex signal processing networks in mammalian cells using RNA interference (RNAi) as the underlying regulatory mechanism.
His areas of interests are in Signal Processing, Networks, and Security.
Advances were made in analytical chemistry and physics instrumentation including improved sensors, optics, tracers, instrumentation, signal processing, networks, robots, satellites, and compute power for data collection, storage, analysis, modeling, visualization, and simulations.
The motifs that are used significantly more often than predicted by chance, as determined by a multiple-hypothesis-corrected test, are easily identified as important elements in a signal-processing network.
