Abstract: A microphone including a casing having a front wall, a back wall, and a side wall joining the front wall to the back wall, a transducer mounted to the front wall, the transducer including a substrate and a transducing element, the transducing element having a transducer acoustic compliance dependent on the transducing element dimensions, a back cavity cooperatively defined between the back wall, the side wall, and the transducer, the back cavity having a back cavity acoustic compliance. The transducing element is dimensioned such that the transducing element length matches a predetermined resonant frequency and the transducing element width, thickness, and elasticity produces a transducer acoustic compliance within a given range of the back cavity acoustic compliance.

Abstract: A transducer includes a first piezoelectric layer; and a second piezoelectric layer that is above the first piezoelectric layer; wherein the second piezoelectric layer is a more compressive layer with an average stress that is less than or more compressive than an average stress of the first piezoelectric layer.

Abstract: A transducer system has a transducer configured to receive an incident signal and produce an output signal as a function of the incident signal. As known in the art, the output signal has a ?3 dB point. The transducer system also has circuitry operatively coupled with the transducer. The circuitry includes an amplifier with an output configured to produce an amplified signal as a function of the output signal. In addition, the circuitry further has a positive feedback loop and a negative feedback loop that both are electrically coupled between the transducer and the amplifier. The positive feedback loop is configured to move the ?3 dB point in a first frequency direction. Conversely, the negative feedback loop is configured to move the ?3 dB point in a second frequency direction. Preferably, the first and second frequency directions are different.

Abstract: A method for annotating points on a 2D image of a hand, includes: capturing several images of the hand from different views; for each viewpoint, the hand is imaged using cameras including: one first 2D camera and one 3D camera; using a 3D engine for: creating a 3D hand representation from the 3D camera; considering a 3D model of an articulated hand with predefined annotation points; considering several 3D viewpoints of the hand; for each viewpoint considered: modifying the articulated hand to be superimposed with the 3D representation; considering a 2D image captured from the first 2D camera; superimposing the modified articulated hand on the hand captured on the 2D image; applying the annotation points of the modified articulated hand on the hand captured on the 2D image; and storing the 2D image with annotation on the hand.

Abstract: Transistor noise tolerant, non-volatile (NV) resistance element-based static random access memory (SRAM) physically unclonable function (PUF) circuits and related systems and methods. In exemplary aspects, a transistor and its complementary transistor, such as a pull-up transistor and complement pull-down transistor or pull-down transistor and complement pull-up transistor, of the PUF circuit are replaced with passive NV resistance elements coupled to the respective output node and complement output node to enhance imbalance between cross-coupled transistors of the PUF circuit for improved PUF output reproducibility. The added passive NV resistance elements replacing pull-up or pull-down transistors in the PUF circuit reduces or eliminates transistor noise that would otherwise occur if the replaced transistors were present in the PUF circuit as a result of changes in temperature, voltage variations, and aging effect.

Abstract: Techniques are provided for selecting a three-dimensional model. An input image including an object can be obtained, and a pose of the object in the input image can be determined. One or more candidate three-dimensional models representing one or more objects in the determined pose can be obtained. From the one or more candidate three-dimensional models, a candidate three-dimensional model can be determined to represent the object in the input image.

Abstract: A fingerprint sensor is described that includes a thin protective cover layer on a sensor glass layer with receive circuitry between the thin protective cover layer and the sensor glass layer. In an implementation, a fingerprint sensor assembly includes a controller; a metal layer configured to be electrically coupled to the controller; a transmit layer electrically connected to the metal layer and the controller; a sensor glass layer, where the transmit layer is disposed on a first side of the sensor glass layer, and where the transmit layer is electrically coupled to the controller; a receive layer disposed on a second side of the sensor glass layer, where the receive layer is electrically coupled to the controller; and a protective cover layer disposed on the receive layer.

Abstract: Apparatus and methods for activity based plasticity in a spiking neuron network adapted to process sensory input. In one approach, the plasticity mechanism of a connection may comprise a causal potentiation portion and an anti-causal portion. The anti-causal portion, corresponding to the input into a neuron occurring after the neuron response, may be configured based on the prior activity of the neuron. When the neuron is in low activity state, the connection, when active, may be potentiated by a base amount. When the neuron activity increases due to another input, the efficacy of the connection, if active, may be reduced proportionally to the neuron activity. Such functionality may enable the network to maintain strong, albeit inactive, connections available for use for extended intervals.

Abstract: Event-based updates in artificial neuron networks may be implemented. An internal event may be defined in order to update incoming connections of a neuron. The internal event may be triggered by an external signal and/or internally by the neuron. A reinforcement signal may be used to trigger an internal event of a neuron in order to perform synaptic updates without necessitating post-synaptic response. An external event may be defined in order to deliver response of the neuron to desired targets. The external and internal events may be combined into a composite event configured to effectuate connection update and spike delivery to post-synaptic target. The scope of the internal event may comprise the respective neuron and does not extend to other neurons of the network. Conversely, the scope of the external event may extend to other neurons of the network via, for example, post-synaptic spike delivery.

Abstract: Apparatus and methods for implementing learning by robotic devices. Attention of the robot may be manipulated by use of a spot-light device illuminating a portion of the aircraft undergoing inspection in order to indicate to inspection robot target areas requiring more detailed inspection. The robot guidance may be aided by way of an additional signal transmitted by the agent to the robot indicating that the object has been illuminated and attention switch may be required. The robot may initiate a search for the signal reflected by the illuminated area requiring its attention. Responsive to detecting the illuminated object and receipt of the additional signal, the robot may develop an association between the two events and the inspection task thereby storing a robotic context. The context of one robot may be shared with other devices in lieu of training so as to enable other devices to perform the task.

Abstract: Apparatus and methods for activity based plasticity in a spiking neuron network adapted to process sensory input. In one approach, the plasticity mechanism of a connection may comprise a causal potentiation portion and an anti-causal portion. The anti-causal portion, corresponding to the input into a neuron occurring after the neuron response, may be configured based on the prior activity of the neuron. When the neuron is in low activity state, the connection, when active, may be potentiated by a base amount. When the neuron activity increases due to another input, the efficacy of the connection, if active, may be reduced proportionally to the neuron activity. Such functionality may enable the network to maintain strong, albeit inactive, connections available for use for extended intervals.

Abstract: Apparatus and methods for event based communication in a spiking neuron network. The network may comprise units communicating by spikes via synapses. The spikes may communicate a payload data. The data may comprise one or more bits. The payload may be stored in a buffer of a pre-synaptic unit and be configured to accessed by the post-synaptic unit. Spikes of different payload may cause different actions by the recipient unit. Sensory input spikes may cause postsynaptic response and trigger connection efficacy update. Teaching input spikes trigger the efficacy update without causing the post-synaptic response.

Abstract: An improved switchable capacitor array comprises a plurality of n?2 capacitor units, each comprising a capacitor with a capacitance and a switch unit. The capacitor units are electrically connected in series. Equidistantly spaced impedance values can be obtained if the values of the capacitances are chosen properly.

Abstract: Apparatus and methods for developing parallel networks. Parallel network design may comprise a general purpose language (GPC) code portion and a network description (ND) portion. GPL tools may be utilized in designing the network. The GPL tools may be configured to produce network specification language (NSL) engine adapted to generate hardware optimized machine executable code corresponding to the network description. The developer may be enabled to describe a parameter of the network. The GPC portion may be automatically updated consistent with the network parameter value. The GPC byte code may be introspected by the NSL engine to provide the underlying source code that may be automatically reinterpreted to produce the hardware optimized machine code. The optimized machine code may be executed in parallel.

Abstract: A simple format is disclosed and referred to as Elementary Network Description (END). The format can fully describe a large-scale neuronal model and embodiments of software or hardware engines to simulate such a model efficiently. The architecture of such neuromorphic engines is optimal for high-performance parallel processing of spiking networks with spike-timing dependent plasticity. Methods for managing memory in a processing system are described whereby memory can be allocated among a plurality of elements and rules configured for each element such that the parallel execution of the spiking networks is most optimal.

Abstract: Apparatus and methods for an extensible robotic device with artificial intelligence and receptive to training controls. In one implementation, a modular robotic system that allows a user to fully select the architecture and capability set of their robotic device is disclosed. The user may add/remove modules as their respective functions are required/obviated. In addition, the artificial intelligence is based on a neuronal network (e.g., spiking neural network), and a behavioral control structure that allows a user to train a robotic device in manner conceptually similar to the mode in which one goes about training a domesticated animal such as a dog or cat (e.g., a positive/negative feedback training paradigm) is used. The trainable behavior control structure is based on the artificial neural network, which simulates the neural/synaptic activity of the brain of a living organism.

Abstract: Efficient updates of connections in artificial neuron networks may be implemented. A framework may be used to describe the connections using a linear synaptic dynamic process, characterized by stable equilibrium. The state of neurons and synapses within the network may be updated, based on inputs and outputs to/from neurons. In some implementations, the updates may be implemented at regular time intervals. In one or more implementations, the updates may be implemented on-demand, based on the network activity (e.g., neuron output and/or input) so as to further reduce computational load associated with the synaptic updates. The connection updates may be decomposed into multiple event-dependent connection change components that may be used to describe connection plasticity change due to neuron input. Using event-dependent connection change components, connection updates may be executed on per neuron basis, as opposed to per-connection basis.

Abstract: The invention is a transaction interface protocol wherein the interface protocol has a transaction identifier signal in each of the request and response channels. It is used between a target network interface unit (NIU) master and an initiator NIU slave that are directly connected through a transaction interface. The target NIU response channel uses the transaction ID signal to identify the entry in a context array associated with the corresponding request. The coupling of target NIU and initiator NIU enable the formation of an on-chip interconnect comprising multiple network-on-chip (NoCs) wherein the topology of the interconnect is simpler, smaller, faster, and has lower latency.

Abstract: Embodiments are directed towards performing depth estimation within a digital camera system based on interpolation of inverse focus statistics. After an image is captured, various statistics or focus measure may be calculated using, for example, a high pass filter. Depth is estimated by interpolating the inverse of the statistics for three positions of focus for the image. The inverse of the statistics, St(n), may be 1/St(n), or 1/St2(n), or even 1/StZ(n), where Z?1. Several approaches to interpolating the inverse values of the statistics to obtain a depth estimate are disclosed, including a general parabolic minimum approach, using a parabolic minimum within a progressive scheme, or within a continuous AF scheme. The depth estimate may then be used for a variety of applications, including automatic focusing, as well as converting 2D images to 3D images.

Abstract: Embodiments are directed towards enabling digital cameras to digitally process captured two dimensional image sequences at a real time video rate, to convert the two dimensional image sequences into stereoscopic three dimensional image sequences. In one embodiment, using a pipelining architecture, various statistics are obtained for a captured two dimensional sequence. The statistics are used to estimate depth within each frame image within the sequence, in real time. Using the depth data a disparity map is generated that is provided to a warping component to generate a second perspective of the two dimensional image. The two images for the frame provide a three dimensional perspective for the frame within the sequence. Together the two perspective images for the frame are provided to a video encoder component to encode the stereoscopic three dimensional frame for the sequence.