943 results about "Signal classification" patented technology

A system and method for managing the spectrum utilization of a frequency band that is shared, both in frequency and time, by multiple devices. At one or more devices operating in the frequency band, pulses associated with signals occurring in the frequency band are detected by sampling part or all the frequency band for a time interval. From the detected signal pulses, the signals can be classified. In addition, overall spectrum activity can be measured. Using classification information for signals detected in the frequency band, policies can be executed so that a device may take certain actions in order to avoid interfering with other signals, or to optimize simultaneous use of the frequency band with the other signals. Signal detection occurs at one or more devices operating in a frequency band. Signal classification and measurement, as well as policy execution may occur within a processor of the same device where signal detection occurs, or in another device (located remotely or within the operating region of the frequency band).

In a method of cognitive communication for non-interfering transmission, wherein the improvement comprises the step of conducting radio scene analysis to find not just the spectrum holes or White spaces; but also to use the signal classification, machine learning and prediction information to learn more things about the existing signals and its underlying protocols, to find the Gray space, hence utilizing the signal space, consisting of space, time, frequency (spectrum), code and location more efficiently.

Methods and systems for dynamic spectrum access (DSA) in a wireless network are provided. A DSA-enabled device may sense spectrum use in a region and, based on the detected spectrum use, select one or more communication channels for use. The devices also may detect one or more other DSA-enabled devices with which they can form DSA networks. A DSA network may monitor spectrum use by cooperative and non-cooperative devices, to dynamically select one or more channels to use for communication while avoiding or reducing interference with other devices.

Disclosed is a unique system and method for recognizing the type of modulation embedded in an unknown complex baseband signal, comprising a receiver section for extracting the complex baseband signal from a modulated signal having a carrier frequency, and comprising an orderly series of signal processing functions for (a) estimating the bandwidth of the unknown signal, (b) removing the out-of-band noise and correcting gross carrier frequency errors, (c) discriminating between constant envelope and irregular envelope signals, (d) estimating and correcting residual carrier frequency errors, (e) classifying a constant envelope signal into one of the following modulation formats: {Continuous Wave (CW), Frequency Modulation (FM), Frequency Shift Keying (FSK)}, and (f) classifying an irregular envelope signal into one of the following modulation formats: {Amplitude Modulation (AM), Double Sideband Suppressed Carrier (DSB-SC), Binary Shift Keying (BPSK), Quaternary Phase Shift Keying (QPSK), π / 4-shifted QPSK, M-ary PSK (MPSK), and OTHER classes}.

Systems and methods for grading signals from microemboli in blood flow monitored using a Doppler ultrasound system. Signals from microemboli in blood flow are graded by calculating a value related to a power for the signals from microemboli in blood flow and categorizing the signals into one of at least two grades based on the calculated value. Alternatively, signals can be categorized by assessing a power value for the microemboli in blood flow during a period of monitoring. In response to the power value being greater than or equal to a threshold value, the microemboli in blood flow are categorized based on the power value, and in response to the power value being less than the threshold value, a number of microemboli are counted during at least a portion of the period of monitoring and the microemboli are categorized based on the number.

The present invention relates to a method and device for improving concealment of frame erasure caused by frames of an encoded sound signal erased during transmission from an encoder (106) to a decoder (110), and for accelerating recovery of the decoder after non erased frames of the encoded sound signal have been received. For that purpose, concealment / recovery parameters are determined in the encoder or decoder. When determined in the encoder (106), the concealment / recovery parameters are transmitted to the decoder (110). In the decoder, erasure frame concealment and decoder recovery is conducted in response to the concealment / recovery parameters. The concealment / recovery parameters may be selected from the group consisting of: a signal classification parameter, an energy information parameter and a phase information parameter. The determination of the concealment / recovery parameters comprises classifying the successive frames of the encoded sound signal as unvoiced, unvoiced transition, voiced transition, voiced, or onset, and this classification is determined on the basis of at least a part of the following parameters: a normalized correlation parameter, a spectral tilt parameter, a signal-to-noise ratio parameter, a pitch stability parameter, a relative frame energy parameter, and a zero crossing parameter.

Systems and methods for grading signals from microemboli in blood flow monitored using a Doppler ultrasound system. Signals from microemboli in blood flow are graded by calculating a value related to a power for the signals from microemboli in blood flow and categorizing the signals into one of at least two grades based on the calculated value. Alternatively, signals can be categorized by assessing a power value for the microemboli in blood flow during a period of monitoring. In response to the power value being greater than or equal to a threshold value, the microemboli in blood flow are categorized based on the power value, and in response to the power value being less than the threshold value, a number of microemboli are counted during at least a portion of the period of monitoring and the microemboli are categorized based on the number.

Provided are a classifying method and apparatus for an audio signal, and an encoding / decoding method and apparatus for an audio signal using the classifying method and apparatus. In the classification method, an audio signal is classified by adaptively adjusting a classification threshold for a frame of the audio signal that is to be classified according to a long-term feature of the audio signal, thereby improving a hit rate of signal classification, suppressing frequent mode switching per frame, improving noise tolerance, and providing smooth reconstruction of the audio signal.

A method and system are disclosed to detect a broad class of signals including Advanced Television Systems Committee (ATSC) digital television (DTV) and wireless microphone signals. This signal detection method performs in Gaussian noise, employing Higher Order Statistics (HOS). Signals are processed in time and frequency domains as well as by real and imaginary components. The spectrum sensing employed also supports Denial of Service (DoS) signal classification. The method can include parameters that may be tailored to adjust the probability of detection and false alarm.

A system classifies the source of an input signal. The system determines whether a sound source belongs to classes that may include human speech, musical instruments, machine noise, or other classes of sound sources. The system is robust, performing classification despite variation in sound level and noise masking. Additionally, the system consumes relatively few computational resources and adapts over time to provide consistently accurate classification.

Encoding audio signals with selecting an encoding mode for encoding the signal categorizing the signal into active segments having voice activity and non-active segments having substantially no voice activity by using categorization parameters depending on the selected encoding mode and encoding at least the active segments using the selected encoding mode.

A system and method whereby acoustic signals can be classified and identified as to nature and location of the original signal. The system and method determine from an arbitrary set of signals a signature or other characterizing feature and distinguish signals associated with a plurality of conditions by means of dictionaries comprising atoms of signals.