Abstract: Sparse representation of information performs powerful feature extraction on high-dimensional data and is of interest for applications in signal processing, machine vision, object recognition, and neurobiology. Sparse coding is a mechanism by which biological neural systems can efficiently process complex sensory data while consuming very little power. Sparse coding algorithms in a bio-inspired approach can be implemented in a crossbar array of memristors (resistive memory devices). This network enables efficient implementation of pattern matching and lateral neuron inhibition, allowing input data to be sparsely encoded using neuron activities and stored dictionary elements. The reconstructed input can be obtained by performing a backward pass through the same crossbar matrix using the neuron activity vector as input. Different dictionary sets can be trained and stored in the same system, depending on the nature of the input signals.

Abstract: Sparse representation of information performs powerful feature extraction on high-dimensional data and is of interest for applications in signal processing, machine vision, object recognition, and neurobiology. Sparse coding is a mechanism by which biological neural systems can efficiently process complex sensory data while consuming very little power. Sparse coding algorithms in a bio-inspired approach can be implemented in a crossbar array of memristors (resistive memory devices). This network enables efficient implementation of pattern matching and lateral neuron inhibition, allowing input data to be sparsely encoded using neuron activities and stored dictionary elements. The reconstructed input can be obtained by performing a backward pass through the same crossbar matrix using the neuron activity vector as input. Different dictionary sets can be trained and stored in the same system, depending on the nature of the input signals.

Abstract: Sparse representation of information performs powerful feature extraction on high-dimensional data and is of interest for applications in signal processing, machine vision, object recognition, and neurobiology. Sparse coding is a mechanism by which biological neural systems can efficiently process complex sensory data while consuming very little power. Sparse coding algorithms in a bio-inspired approach can be implemented in a crossbar array of memristors (resistive memory devices). This network enables efficient implementation of pattern matching and lateral neuron inhibition, allowing input data to be sparsely encoded using neuron activities and stored dictionary elements. The reconstructed input can be obtained by performing a backward pass through the same crossbar matrix using the neuron activity vector as input. Different dictionary sets can be trained and stored in the same system, depending on the nature of the input signals.

Abstract: Sparse representation of information performs powerful feature extraction on high-dimensional data and is of interest for applications in signal processing, machine vision, object recognition, and neurobiology. Sparse coding is a mechanism by which biological neural systems can efficiently process complex sensory data while consuming very little power. Sparse coding algorithms in a bio-inspired approach can be implemented in a crossbar array of memristors (resistive memory devices). This network enables efficient implementation of pattern matching and lateral neuron inhibition, allowing input data to be sparsely encoded using neuron activities and stored dictionary elements. The reconstructed input can be obtained by performing a backward pass through the same crossbar matrix using the neuron activity vector as input. Different dictionary sets can be trained and stored in the same system, depending on the nature of the input signals.

Abstract: Sparse representation of information performs powerful feature extraction on high-dimensional data and is of interest for applications in signal processing, machine vision, object recognition, and neurobiology. Sparse coding is a mechanism by which biological neural systems can efficiently process complex sensory data while consuming very little power. Sparse coding algorithms in a bio-inspired approach can be implemented in a crossbar array of memristors (resistive memory devices). This network enables efficient implementation of pattern matching and lateral neuron inhibition, allowing input data to be sparsely encoded using neuron activities and stored dictionary elements. The reconstructed input can be obtained by performing a backward pass through the same crossbar matrix using the neuron activity vector as input. Different dictionary sets can be trained and stored in the same system, depending on the nature of the input signals.

Abstract: Sparse representation of information performs powerful feature extraction on high-dimensional data and is of interest for applications in signal processing, machine vision, object recognition, and neurobiology. Sparse coding is a mechanism by which biological neural systems can efficiently process complex sensory data while consuming very little power. Sparse coding algorithms in a bio-inspired approach can be implemented in a crossbar array of memristors (resistive memory devices). This network enables efficient implementation of pattern matching and lateral neuron inhibition, allowing input data to be sparsely encoded using neuron activities and stored dictionary elements. The reconstructed input can be obtained by performing a backward pass through the same crossbar matrix using the neuron activity vector as input. Different dictionary sets can be trained and stored in the same system, depending on the nature of the input signals.

Abstract: A two piece helmet with optional airbag is split along a vertical axis between the sides of the helmet to ease removal in the event of an injury. A series of aligned orifices in the helmet portions are joined by a removable cable. The cable ends are attached to each other to secure the helmet portions or to each of the helmet portions. The cable is accessed through removable panels that may also be used to tension the cable. Alternate means for joining the helmet portions include a series of lateral exterior latches opened by the cable. The helmet liner has two overlapping portions to minimize noise and improve weather sealing. An optional inflatable air bag is fitted to a lower perimeter of the helmet. A proximity sensing system will inflate the airbag when the vehicle is in motion and the helmet is displaced a certain distance from the vehicle.

Abstract: A bubble forming mechanism has a bottle for holding therein a bubble forming solution. The bottle has a concave top surface with a slot formed in the surface. The bottle also includes a guide carried by a portion of the bottle. The mechanism has a wand with a loop carried on a lower end of the wand wherein the wand and loop are capable of being received in the slot and into the bottle. The guide aligns the wand and the loop with the slot.

Abstract: A bubble forming mechanism has a bottle for holding therein a bubble forming solution. The bottle has a concave top surface with a slot formed in the surface. The bottle also includes a guide carried by a portion of the bottle. The mechanism has a wand with a loop carried on a lower end of the wand wherein the wand and loop are capable of being received in the slot and into the bottle. The guide aligns the wand and the loop with the slot.

Abstract: Nucleic acid probes are immobilized on polystyrene surfaces such as the wells of microtiter plates for use in solution phase nucleic acid sandwich hybridization assays, particularly those using large branched DNA amplification multimers, by: (a) cleansing the surface by washing it sequentially with a strong acid, a strong base, and water, (b) passively adsorbing a polypeptide having primary amino groups onto the cleansed surface, and (c) covalently bonding the probe to the adsorbed polypeptide via a base-stable bifunctional crosslinking agent, and (d) subjecting the surface to conditions that simulate the hybridization conditions used in the assay.

Abstract: Nucleic acid probes are immobilized on polystyrene surfaces such as the wells of microtiter plates for use in solution phase nucleic acid sandwich hybridization assays, particularly those using large branched DNA amplification multimers, by: (a) cleansing the surface by washing it sequentially with a strong acid, a strong base, and water, (b) passively adsorbing a polypeptide having primary amino groups onto the cleansed surface, and (c) covalently bonding the probe to the adsorbed polypeptide via a base-stable bifunctional crosslinking agent, and (d) subjecting the surface to conditions that simulate the hybridization conditions used in the assay.