Any one or both of an optical system with a structured lighting pattern and a structured detecting system having a plurality of regions with different optical characteristics are used. In addition, optical signals from an object to be observed through one or a small number of pixel detectors are detected while changing relative positions between the object to be observed and any one of the optical system and the detecting system, time series signal information of the optical signals are obtained, and an image associated with an object to be observed from the time series signal information is reconstructed.

The redundancy in genomic sequence data is exploited by compressing sequence data in such a way as to allow direct computation on the compressed data using methods that are referred to herein as compressive algorithms. This approach reduces the task of computing on many similar genomes to only slightly more than that of operating on just one. In this approach, the redundancy among genomes is translated into computational acceleration by storing genomes in a compressed format that respects the structure of similarities and differences important to analysis. Specifically, these differences are the nucleotide substitutions, insertions, deletions, and rearrangements introduced by evolution. Once such a compressed library has been created, analysis is performed on it in time proportional to its compressed size, rather than having to reconstruct the full data set every time one wishes to query it.

Hyperspectral imaging spectrometers have applications in environmental monitoring, biomedical imaging, surveillance, biological or chemical hazard detection, agriculture, and minerology. Nevertheless, their high cost and complexity has limited the number of fielded spaceborne hyperspectral imagers. To address these challenges, the wide field-of-view (FOV) hyperspectral imaging spectrometers disclosed here use computational imaging techniques to get high performance from smaller, noisier, and less-expensive components (e.g., uncooled microbolometers). They use platform motion and spectrally coded focal-plane masks to temporally modulate the optical spectrum, enabling simultaneous measurement of multiple spectral bins. Demodulation of this coded pattern returns an optical spectrum in each pixel. As a result, these computational reconfigurable imaging spectrometers are more suitable for small space and air platforms with strict size, weight, and power constraints, as well as applications where smaller or less expensive packaging is desired.

The present disclosure is directed to a snapshot multiframe imager having an aperture element having at least one aperture, an adjacently positioned random mask, an imaging element and a computer. The random mask has a plurality of micron scale apertures and receives light passing through the aperture element, which represents the spatial information from the scene being imaged, and generates a plurality of image frames encoded in a spatial domain. The imaging element may operate in a drift-scan mode receives the encoded image frames and generates a streaked pattern of electrons representing a plurality of images of the scene at a plurality of different times. The computer analyzes the streaked pattern of electrons and mathematically reconstructs the plurality of images.

A sensor device comprising a computational memory and electronic circuitry. The sensor device is configured to receive an input signal, to compress the input signal into a compressed signal and to compute a reconstructed signal from the compressed signal. The electronic circuitry is configured to perform a reconstruction algorithm to compute the reconstructed signal. The computational memory is configured to compute the compressed signal and partial results of the reconstruction algorithm. A related method and a related design structure may be provided.

According to various embodiments, an Internet of Things (IoT) sensor architecture is disclosed. The architecture includes one or more IoT sensor components configured to capture data and one or more processors configured to analyze the captured data. The processors include a data compression module configured to convert received data into compressed data, a machine learning module configured to extract features from the received data and classify the extracted features, and an encryption/hashing module configured to encrypt and ensure integrity of resulting data from the machine learning module or the received data.

A security device for hindering data theft and data leaks via audio channel of a computer system is based on passing the audio signals through a coding vocoder that receives input audio signal from a computer and compressing the signal to a low bit-rate digital data indicative of human speech; and a decoding vocoder that decompress the digital data back to a secure audio signal. The data transfer of the protected audio channel is intentionally limited not to exceed the bit-rate needed to carry vocoder-compressed human speech which is well below the capabilities of unprotected audio channel. Both analog and digital audio ports may be protected. Hardware bit-rate limiter protect the system from software hacking.

Any one or both of an optical system with a structured lighting pattern and a structured detecting system having a plurality of regions with different optical characteristics are used. In addition, optical signals from an object to be observed through one or a small number of pixel detectors are detected while changing relative positions between the object to be observed and any one of the optical system and the detecting system, time series signal information of the optical signals are obtained, and an image associated with an object to be observed from the time series signal information is reconstructed.

A compressive sensing image sensor includes: a pixel array; and a readout circuit configured to receive pixel data on a shot image in an analogue form, and to process the pixel data, wherein the pixel array includes a plurality of blocks each having a plurality of pixels and arranged in an array form, wherein the circuit includes: a compressive sensing multiplexer to which a plurality of pixel data outputted from a corresponding block from among the plurality of blocks are inputted; an LFSR configured to arbitrarily select at least one pixel data from the plurality of pixel data inputted to the compressive sensing multiplexer; and a delta-sigma ADC configured to receive the at least one pixel data selected by the LFSR, to delta-sigma modulate the received at least one pixel data, and to generate compressive sensing data for restoring an image of the corresponding block from among the shot images.

An apparatus includes data acquisition circuitry and a processor. The data acquisition circuitry is configured to acquire multiple signals using multiple respective electrodes of an array of electrodes coupled to one of an organ of a patient and tissue or a cell culture. The processor is configured to hold a definition of a mixed-norm that is defined as a function of relative positions of the electrodes in the array, and jointly compress the multiple signals in a compressed-sensing (CS) process that minimizes the mixed-norm.