Motivated by the many applications associated with estimation of sparse multivariate models, the estimation of sparse directional connectivity between the imperfectly measured nodes of a network is studied. Node dynamics and interactions are assumed to follow a multivariate autoregressive model driven by noise, and the observations are a noisy linear combination of the underlying node activities.
We consider the problem of detecting the presence of a complex-valued, possibly improper, but unknown signal, common among two or more sensors (channels) in the presence of spatially independent, unknown, possibly improper and colored, noise. Past work on this problem is limited to signals observed in proper noise.
In the last decade, a large number of techniques have been proposed to ensure integrity and authenticity of data in security-oriented applications, e.g. multime-dia forensics, biometrics, watermarking and information hiding, network intrusion detection, reputation systems, etc.... The development of these methods has re-ceived a new boost in the last few years with the advent of Deep Learning (DL) techniques and Convolutional Neural Networks (CNNs).
The International Institute for Smart Transportation, Infrastructure, Finance and Computing (IISTIFC) affiliated with the School of Smart Cities (SSC) at South China University of Technology (SCUT), Guangzhou, China invites applicants to fill three-year term non-tenure track Research Assistant Professor positions on Guangzhou International Campus for conducting interdisciplinary engineering education and cutting-edge research.
If you’ve ever been to the emergency room due to an injury, chances are you’ve had a routine encounter with what is in fact a wonder of the modern age: Magnetic Resonance Imaging, or MRI. Advancements in medical imaging allow us to study parts of the body, including the brain, to an extent unprecedented in the history of medical science.
We design, create and build outstanding experiences by developing and implementing new algorithms at the intersection of audio, voice, DSP, multimodal interfaces and new technologies.
What You’ll Do
• You will research, design, and prototype future Sonos systems and algorithms.
• You will collaborate with Audio Systems Engineering, EE HW, User Experience and various SW teams.
• You will drive innovation and push the boundaries of what we can achieve with human machine interaction and focus on speech and audio.
• You are confident in the state o