Texas Instruments Corporation

National Semiconductor Corporation

Zhenyong Zhang

Wei Ma

Mark Kuhns

Jian-Yi Wu

Mikko Topi Loikkanen

Ahmad Reza Bahai

Bozhao Tan

Masood Yousefi

Shougang Wang

A sound recognition system including time-dependent analog filtered feature extraction and sequencing. An analog front end (AFE) in the system receives input analog signals, such as signals representing an audio input to a microphone. Features in the input signal are extracted, by measuring such attributes as zero crossing events and total energy in filtered versions of the signal with different frequency characteristics at different times during the audio event. In one embodiment, a tunable analog filter is controlled to change its frequency characteristics at different times during the event. In another embodiment, multiple analog filters with different filter characteristics filter the input signal in parallel, and signal features are extracted from each filtered signal; a multiplexer selects the desired features at different times during the event.

Time-based frequency tuning of analog-to-information feature extraction

A system includes an analog-to-digital converter receiving input signals. One particular input signal has a particular analog value, and the analog-to-digital converter uses a fixed reference to convert the particular analog value to a particular digital value. The analog-to-digital converter uses the particular analog value as a reference for converting the analog values of the remaining input signals.

Analog-to-digital converter

A duty-cycled acoustic sensor saves power, for example, by operating for relatively short periods of time in a repetitive manner. A sensor bias current provides operating power to the sensor. An output analog signal from the sensor carries the information induced by the sensor upon the bias signal. Capacitive coupling is employed to remove direct DC voltage from the output analog signal to generate an analog input signal for acoustic analysis. A capacitor for capacitive coupling is pre-charged to reduce the charging time of the capacitor as the sensor is being powered up. After the capacitor is sufficiently precharged, acoustic analysis is performed on the analog input signal. The sensor is powered down by substantially blocking current flow through the sensor, which saves power. Results of the acoustic analysis can be used, for example, to control parameters of the duty-cycling of the acoustic sensor.

Duty-cycling microphone/sensor for acoustic analysis

A low power sound recognition sensor is configured to receive an analog signal that may contain a signature sound. Sparse sound parameter information is extracted from the analog signal and compared to a sound parameter reference stored locally with the sound recognition sensor to detect when the signature sound is received in the analog signal. A portion of the sparse sound parameter information is differential zero crossing (ZC) counts. Differential ZC rate may be determined by measuring a number of times the analog signal crosses a threshold value during each of a sequence of time frames to form a sequence of ZC counts and taking a difference between selected pairs of ZC counts to form a sequence of differential ZC counts.

Robust feature extraction using differential zero-crossing counts

A system includes an analog-to-digital converter receiving a plurality of input signals. One particular input signal has a particular analog value and the analog-to-digital converter uses a fixed reference to convert the particular analog value to a particular digital value. The analog-to-digital converter uses the particular analog value as a reference for converting the analog values of the remaining input signals.

Comparing differential ZC count to database to detect expected sound

A low power sound recognition sensor is configured to receive an analog signal that may contain a signature sound. The received analog signal is evaluated using a detection portion of the analog section to determine when background noise on the analog signal is exceeded. A feature extraction portion of the analog section is triggered to extract sparse sound parameter information from the analog signal when the background noise is exceeded. An initial truncated portion of the sound parameter information is compared to a truncated sound parameter database stored locally with the sound recognition sensor to detect when there is a likelihood that the expected sound is being received in the analog signal. A trigger signal is generated to trigger classification logic when the likelihood that the expected sound is being received exceeds a threshold value.

Powering-up AFE and microcontroller after comparing analog and truncated sounds

Multi-channel receiver circuitry for a sub-beam forming receiver of an ultrasound system in which digital filtering, down-sampling and successive data storage circuitry impose programmable fine and coarse time delays on received digital data signals.

Sub-beam forming receiver circuitry for ultrasound system

Multi-channel pulser driver circuitry for a sub-beam forming transmitter of an ultrasound system in which sub-beam signals are formed by delaying sub-beam pulse pattern data in accordance with sub-beam pulse delay data and multiple clock signals.

Sub-beam forming transmitter circuitry for ultrasound system

A signal integrator and method for integrating a continuous current and a discrete charge in which the discrete charge is provided for integration during multiple overlapping time intervals.

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San Jose, CA, United States of America

Zhenyong Zhang