Abstract: Disclosed herein are systems and methods for removing reverberation from signals. The systems and methods can be applicable to audio signals, for example, to voice, musical instrument sounds, and the like. Signals such as the vowel sounds in speech and the sustained portions of many musical instrument sounds can be composed of a fundamental frequency component and a series of harmonically related overtones. The systems and methods can exploit the intrinsically high degree of mutual correlation among the overtones. When such signals are passed through a reverberant channel, the degree of mutual correlation among the partials can be reduced. An inverse channel filter for the removal of reverberation can be found by employing an adaptive filter technique that maximizes the cross-correlation among signal overtones.

Abstract: An automated system for monitoring respiratory diseases, such as asthma, provides noninvasive, multimodal monitoring of respiratory signs and symptoms that can include wheeze and cough. Some embodiments employ a mobile device, such as a cell phone, in which raw data from a microphone and an accelerometer are processed, analyzed, and stored. Data can be collected continuously. Time domain and frequency domain analyses of signals to determine, e.g., energy, duration, and spectral content of candidate sounds can be employed to discriminate symptoms of interest from background sounds and to establish significance. Accelerometer signals are analyzed to determine activity levels. Analyses of a user's symptoms and activity level prior to, during, and after an event can provide meaningful determinations of disease severity and predict future respiratory events. The system can provide a summary of data, as well as an alarm when symptom severity reaches a threshold.

Abstract: An automated system for monitoring respiratory diseases, such as asthma, provides noninvasive, multimodal monitoring of respiratory signs and symptoms that can include wheeze and cough. Some embodiments employ a mobile device, such as a cell phone, in which raw data from a microphone and an accelerometer are processed, analyzed, and stored. Data can be collected continuously. Time domain and frequency domain analyses of signals to determine, e.g., energy, duration, and spectral content of candidate sounds can be employed to discriminate symptoms of interest from background sounds and to establish significance. Accelerometer signals are analyzed to determine activity levels. Analyses of a user's symptoms and activity level prior to, during, and after an event can provide meaningful determinations of disease severity and predict future respiratory events. The system can provide a summary of data, as well as an alarm when symptom severity reaches a threshold.

Abstract: An image-sensing element has an array of photodiodes or other photodetecting elements and performs sigma-delta analog-to-digital conversion on the outputs of the photodetecting elements. The sigma-delta analog-to-digital converters have components divided between pixel-level and row-level structures, with each row-level structure connected to its pixel-level structures to define a multiplexed-input-separated sigma-delta analog-to-digital converter. The converter can include an integrator or can rely on an integration effect of the photodetecting element. The feedback required for sigma-delta analog-to-digital conversion can involve digital-to-analog converters located at each row-level structure or at each pixel-level structure.

Abstract: Data are embedded in an audio signal for watermarking, steganography, or other purposes. The audio signal is divided into time frames. In each time frame, the relative phases of one or more frequency bands are shifted to represent the data to be embedded. In one embodiment, two frequency bands are selected according to a pseudo-random sequence, and their relative phase is shifted. In another embodiment, the phases of one or more overtones relative to the fundamental tone are quantized.