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Live musical performances (e.g., choruses, concerts, and operas) often require the display of lyrics for the convenience of the audience. This requires following the performance and controlling the lyrics display in real time. In practice, this is usually controlled by a staff member of the concert who has been very familiar with the performance. In this paper, we present our effort in implementing a computational system to automate this real-time lyric display process using music following techniques.

We define micro hand gesture recognition system as which uses micro dynamic hand gestures within a time interval for classification and recognition to achieve human-machine interaction. Our Project Hug (Hand-Ultrasonic-Gesture), with ultrasonic active sensing, pulsed radar signal processing, and time-sequence pattern recognition is presented in this paper for micro hand gesture recognition. We leverage one single channel to detect both range and velocity precisely, reducing the hardware complexity.

Current solutions for below the elbow amputees include affordable prosthesis allowing only a single movement or highly expensive prosthesis allowing several gestures. In this project, our goal was to design a system that provides an inexpensive, multi-functional solution for the hand prosthesis problem. We construct a real-time, portable system based on the Myo armband and a 3D printed prosthesis and show that this framework can provide a good and inexpensive solution for below the elbow amputees of all ages.

In this tutorial, we describe how to design a Whole Sky Imager from off-the-shelf components. Subsequently, we use signal processing techniques to derive instantaneous cloud coverage value from the captured images.

This paper presents methods to analyze functional brain networks and signals from graph spectral perspectives. The notion of frequency and filters traditionally defined for signals supported on regular domains such as discrete time and image grids has been recently generalized to irregular graph domains, and defines brain graph frequencies associated with different levels of spatial smoothness across the brain regions. Brain network frequency also enables the decomposition of brain signals into pieces corresponding to smooth or rapid variations.

Sampling and estimation of spatial fields using sensors which are location unaware is an exciting
topic. Here we study this topic under the assumption that the sensors are deployed according
to a known probability distribution, under different scenarios.
The initial part of this work studies detection of bandlimited fields from location-unaware
sensors that are restricted to a discrete grid. Oversampling is used to overcome the lack of
location information. The samples obtained from location-unaware sensors are clustered together

Testing complex digital signal processors (DSPs) requires a development platform with sufficient
signal bandwidth and system performance to fully exercise the DSP. Without a development plat-
form, verification of DSPs would be limited to monitoring test output signals for an indication of
performance and successful operation. In addition, a development platform with high-speed analog
input and output interfaces to the DSP system allows it to be used directly in many sophisticated

Transmitting energy and information simultaneously using orthogonal frequency-division multiplexing (OFDM) to obtain receiver energy self-sufficiency has recently been proposed.To obtain smooth energy delivery, this project analyzes a new architecture for self-sustainable OFDM transmissions that reduces the peak-to-average power ratio (PAPR) in the cyclic prefix through a frame-theoretic operation that modifies the erasure pattern selection technique.