An apparatus, method, or computer-readable storage medium encoded with computer-executable instructions that, when executed by a computer, cause the computer to carry out a method for determining one or more directions of arrival of one or more coherent or incoherent signals with a single radio frequency channel. The apparatus may comprise: a plurality of antenna elements (110) configured to determine the one or more coherent or incoherent signals; a plurality of radio frequency switches (120) configured to selectively activate one or more of the plurality of antenna elements; and a radio frequency combiner (140) configured to combine a plurality of radio frequency signals from one or more selectively activated antenna elements of the plurality of antenna elements.

A tactile reproduction system is made more efficient by achieving a data amount reduction of a tactile signal while ensuring reproducibility of a tactile sense.

A decoding apparatus according to the present technology includes a decoding unit configured to decode tactile coded data obtained by performing encoding of compressing an information amount, on a tactile signal using higher-order perception in a tactile sense. Therefore, a data amount reduction of a tactile signal can be performed in accordance with a tactile characteristic of a human.

A computer-executable method and system for querying sensor data of a plurality of sensors is provided. Sensor data is received that comprising sensor data values sampled by a first sensor of said plurality of sensors according to a first compressive sampling scheme. The first compressive sampling scheme can be applied by the first sensor within a sampling time window and the received sensor data corresponds to samples of a signal within the sampling time window. The sensor data is stored in a first database. A frequency decomposition of the signal is computed based on a sparsifying transform associated with the first compressive sampling scheme and the received sensor data. The frequency decomposition comprises one or more frequency components. The one or more frequency components are stored in a second database. A query is received from a client. The query specifies an event that indicates a critical signal condition of a signal. It is detected whether the event exists using the received sensor data or the one or more frequency components.

A device and computer-executable method is provided for adaptively determining a sampling scheme to be applied at a first sensor from among a plurality of sensors for sampling sensor data values corresponding to a signal. A sparsifying transform for a subsequent sampling time window of the first sensor is predicted, wherein the sparsifying transform is determined based on a predictive model of the sparsity of the signal. Moreover, a subsampling parameter for the subsequent sampling time window is determined. The subsampling parameter corresponds to a number of sensor data values to be acquired within the sampling time window. This subsampling parameter is determined based on the predicted sparsifying transform. Further determined is a compressive sampling scheme for the subsequent sampling time window of the first sensor. The compressive sampling scheme is determined based on the predicted sparsifying transform.

A computer-executable method and system for querying sensor data of a plurality of sensors is provided. Sensor data is received that comprising sensor data values sampled by a first sensor of said plurality of sensors according to a first compressive sampling scheme. The first compressive sampling scheme can be applied by the first sensor within a sampling time window and the received sensor data corresponds to samples of a signal within the sampling time window. The sensor data is stored in a first database. A frequency decomposition of the signal is computed based on a sparsifying transform associated with the first compressive sampling scheme and the received sensor data. The frequency decomposition comprises one or more frequency components. The one or more frequency components are stored in a second database. A query is received from a client. The query specifies an event that indicates a critical signal condition of a signal. It is detected whether the event exists using the received sensor data or the one or more frequency components.

The present application discloses a signal sampling and recovery method and apparatus applicable to an OvXDM system, and the OvXDM system. The method includes: constructing, based on design parameters, an observation matrix Φ that is irrelevant to an original signal y, wherein the observation matrix Φ is a two-dimensional M*S matrix, S is a length of the original signal y, and M is smaller than S; compressing the original signal y based on a formula Y.sub.cs=ΦY, to obtain a M*1 compressed signal Y.sub.cs, wherein Y is a S*1 column vector that is obtained according to the original signal y; and reconstructing the compressed signal Y.sub.cs based on a predetermined algorithm, so as to recover the original signal y. The present application implements accurate recovery of the original signal at a reduced sampling rate, thereby reducing hardware requirements of the system and improving feasibility of the technical solution.

Provided is a data management system which includes a data acquisition unit configured to acquire measurement data obtained by measuring a measurement target, a data storage unit configured to store the acquired measurement data, a data size reduction unit configured to deletes at least a part of the stored measurement data to reduce a data size of the measurement data, and a data compression unit configured to perform data compression on the measurement data reduced in data size.

A compression ratio (CR) adapter (CRA) for end-to-end data-driven compressive sensing (CS) reconstruction (EDCSR) frameworks is provided. EDCSR frameworks achieve state-of-the-art reconstruction performance in terms of reconstruction speed and accuracy for images and other signals. However, existing EDCSR frameworks cannot adapt to a variable CR. For applications that desire a variable CR, existing EDCSR frameworks must be trained from scratch at each CR, which is computationally costly and time-consuming. Embodiments described herein present a CRA framework that addresses the variable CR problem generally for existing and future EDCSR frameworks with no modification to given reconstruction models nor enormous additional rounds of training needed. The CRA exploits an initial reconstruction network to generate an initial estimate of reconstruction results based on a small portion of acquired image measurements. Subsequently, the CRA approximates full measurements for the main reconstruction network by complementing the sensed measurements with a re-sensed initial estimate.

Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications.

An encoding apparatus for encoding a vibrotactile signal includes a first transforming unit configured to perform a discrete wavelet transform of the signal, a second transforming unit configured to generate a frequency domain representation of the signal, a psychohaptic model unit configured to generate at least one quantization control signal based on the generated frequency domain representation of the sampled signal and on a predetermined perceptual model based on human haptic perception, a quantization unit configured to quantize wavelet coefficients resulting from the performed discrete wavelet transform and adapted by the quantization control signal, a compression unit configured to compress the quantized wavelet coefficients, and a bitstream generating unit configured to generate a bitstream corresponding to the encoded signal based on the compressed quantized wavelet coefficients. The subject matter described herein also includes a corresponding decoding unit, an encoding method and a decoding method.