Abstract: An analog memory device includes a first node and a second node. The first node includes a first floating gate, a second floating gate, and a capacitor. The first node first floating gate is connected to the first node second floating gate via the capacitor. The second node includes a first floating gate, a second floating gate, and a capacitor. The second node first floating gate is connected to the second node second floating gate via the capacitor. The second node is connected to the first node, and an analog state of the first node and an analog state of the second node continuously and synchronously decay with respect to time.

Abstract: A self-capacitance based remote power delivery device includes a power source, an energy harvesting device, and a substrate. The power source and the energy harvesting device are configured to be capacitively coupled to a self-capacitive body. The substrate is configured to be capacitively coupled to a portion of the self-capacitive body in contact with the substrate.

Abstract: A sensor blockchain system is provided. The sensor blockchain system includes a plurality of sensor-data-loggers, wherein each sensor-data-logger includes a memory device which utilizes FN tunneling. An input to the sensing interface alters the geometry of the energy barrier to change the electron leakage rate and the current state of the sensor-data logger is determined by an initial state of the sensor-data-logger, the predetermined electron leakage rate, and any inputs to the sensing interface. The sensor-data-loggers may be synchronized to an initial state. The synchronization will be maintained when they are all subjected to similar changes in environmental conditions in a supply chain. Desynchronization will occur due to changes in environment, including changes in temperature.

Abstract: Growth-transform (GT) neurons and their population models allow for independent control over spiking statistics and transient population dynamics while optimizing a physically plausible distributed energy functional involving continuous-valued neural variables. A backpropagation-less learning approach trains a GT network of spiking GT neurons by enforcing sparsity constraints on network spiking activity overall. Spike responses are generated because of constraint violations. Optimal parameters for a given task is learned using neurally relevant local learning rules and in an online manner. The GT network optimizes itself to encode the solution with as few spikes as possible and operate at a solution with the maximum dynamic range and away from saturation. Further, the framework is flexible enough to incorporate additional structural and connectivity constraints on the GT network.

Abstract: A one-time self-powered timer circuit whose state can be measured only once, after which the timer will de-synchronize itself. In this manner, the timers can only be used for one-pad authentication. The security of the public-key distribution algorithms that will exploit the synchronization between billions of hardware-software timers, time reversibility of software timer and time irre-versibility of hardware timers and one-time read-out to deliver classical and quantum-like benefits. System-on-chip and circuit imple-mentation of the self-powered timer array, read-out, programming and initialization modules that implements the proposed public-key distribution algorithms.

Abstract: A sensor system includes a sensor module that is embedded in a target environment and a signal system. The sensor module includes an active sensor of a first type that detects a target element in the target environment and a reference sensor of the first type that prevents detection of target elements by the reference sensor. The active sensor and the reference sensor receive an ultrasonic signal and respectively generate a first response signal and a second response signal. The first response signal is at least partially as a function of the detected target element. The signal system includes an ultrasonic transducer that generates the ultrasonic signal and receives the first and second response signals, and a controller communicatively coupled to the ultrasonic transducer. The controller identifies the detected target element based at least partially on the first and second response signals.

Abstract: A self-capacitance based remote power delivery device includes a power source, an energy harvesting device, and a substrate. The power source and the energy harvesting device are configured to be capacitively coupled to a self-capacitive body. The substrate is configured to be capacitively coupled to a portion of the self-capacitive body in contact with the substrate.

Abstract: A self-capacitance based remote power delivery device includes a modulating power source electrically coupled to a grounded substrate, an energy harvesting device coupled to the grounded substrate, and the substrate. The modulating power source is configured to be capacitively coupled to a self-capacitive body. The energy harvesting device configured to be capacitively coupled to the self-capacitive body, and the substrate is configured to be capacitively coupled to a portion of the self-capacitive body in direct contact with the substrate.

Abstract: The present disclosure is directed to refreshable biosensors and methods for synthesizing and refreshing same. In some embodiments, the refreshable biosensor comprises a plasmonic nanoparticle and a biorecognition element, wherein the biorecognition element is encapsulated with at least one of an organosilica polymer layer or a metal organic framework (MOF).

Abstract: A sensor system for detecting events includes an array of memory devices and a read-out interface. Each memory device includes a floating-gate with a sensing interface, the sensing interface having an energy barrier configured to leak electrons at a predetermined electron leakage rate through Fowler-Nordheim (F-N) tunneling. An input to the sensing interface is configured to alter a geometry of the energy barrier to change the electron leakage rate. The read-out interface is communicatively coupled to at least one memory device, and is configured to retrieve data stored on the at least one memory device for analysis.

Abstract: Devices, systems, and methods related to an energy-efficient machine learning framework which exploits structural and functional similarities between a machine learning network and a general electrical network satisfying the Tellegen's theorem are described.

Abstract: A sensor system for detecting events is provided. The sensor system includes a sensor and a read-out interface. The sensor includes a transducer and a memory device. The transducer detects an event and generates a sensor signal in response to the event. The memory device includes a floating-gate with a sensing interface coupled to the transducer. The sensing interface has an energy barrier that leaks electrons at a predetermined electron leakage rate through Fowler-Nordheim (F-N) tunneling. The sensor signal alters a geometry of the energy barrier to change the electron leakage rate. The read-out interface is communicatively coupled to the memory device and retrieves data stored on the memory device for analysis. The event and a timestamp of the event are identifiable from the stored data.

Abstract: A spiking neural network includes a plurality of neurons implemented in respective circuits. Each neuron produces a continuous-valued membrane potential according to a Growth Transform bounded by an extrinsic energy constraint. The continuous-valued membrane potential is defined as a function of spiking current received from another neuron in the plurality of neurons, and a received electrical current stimulus. The spiking neural network includes a network energy function representing network energy consumed by the plurality of neurons and a neuromorphic framework.

Abstract: A hybrid-powered sensing device is disclosed that includes a power source coupled to a sensing module via an RF-triggered load switching module.

Abstract: A self-capacitance based remote power delivery device includes a modulating power source electrically coupled to a grounded substrate, an energy harvesting device coupled to the grounded substrate, and the substrate. The modulating power source is configured to be capacitively coupled to a self-capacitive body. The energy harvesting device configured to be capacitively coupled to the self-capacitive body, and the substrate is configured to be capacitively coupled to a portion of the self-capacitive body in direct contact with the substrate.

Abstract: A variance-based substrate computing system is disclosed. The variance-based computing system includes a sensor configured to be embedded in a structure, the sensor further configured to generate an electrical output signal in response to a mechanical input, and a processor configured to receive the electrical output signal. The processor includes a measurement module configured to determine a variance of the electrical output signal about a base value, and a transformation module configured to generate a binary output signal based upon the variance.

Abstract: A growth transform neural network system is disclosed that includes a computing device with at least one processor and a memory storing a plurality of modules, including a growth transform neural network module, a growth transform module, and a network convergence module. The growth transform neural network module defines a plurality of mirrored neuron pairs that include a plurality of first components and a plurality of second components. Each first and second component is connected by a normalization link. The first components are interconnected according to an interconnection matrix, and the second components are interconnected according to the interconnection matrix. The growth transform module updates each first component of each mirrored neuron pair according to a growth transform neuron model. The network convergence module converges the plurality of mirrored neuron pairs to a steady state condition by solving a system objective function subject to at least one normalization constraint.

Abstract: A timer module including a timer and a compensation circuit coupled to the timer is provided. The timer measures time over a first monitoring period. The timer includes a floating-gate and an energy barrier. The floating-gate stores electrons and has an initial state and a measured state. The measured state includes a current time and a current floating-gate voltage. The energy barrier is positioned adjacent the floating-gate and leaks electrons from an ambient environment of the timer to the floating-gate at a predetermined leakage rate using Fowler-Nordheim (FN) tunneling. The compensation circuit selectably adjusts the first monitoring period to facilitate improved robustness of the timer with respect to fabrication mismatch due to the self-compensating dynamics of FN tunneling.

Abstract: A sensor system for detecting events is provided. The sensor system includes a sensor and a read-out interface. The sensor includes a transducer and a memory device. The transducer detects an event and generates a sensor signal in response to the event. The memory device includes a floating-gate with a sensing interface coupled to the transducer. The sensing interface has an energy barrier that leaks electrons at a predetermined electron leakage rate through Fowler-Nordheim (F-N) tunneling. The sensor signal alters a geometry of the energy barrier to change the electron leakage rate. The read-out interface is communicatively coupled to the memory device and retrieves data stored on the memory device for analysis. The event and a timestamp of the event are identifiable from the stored data.

Abstract: A sensor system includes a sensor module that is embedded in a target environment and a signal system. The sensor module includes an active sensor of a first type that detects a target element in the target environment and a reference sensor of the first type that prevents detection of target elements by the reference sensor. The active sensor and the reference sensor receive an ultrasonic signal and respectively generate a first response signal and a second response signal. The first response signal is at least partially as a function of the detected target element. The signal system includes an ultrasonic transducer that generates the ultrasonic signal and receives the first and second response signals, and a controller communicatively coupled to the ultrasonic transducer. The controller identifies the detected target element based at least partially on the first and second response signals.