Abstract: Techniques for efficiently performing full and scaled transforms on data received via full and scaled interfaces, respectively, are described and comprise (1) performing a first transform on a block of first input values to obtain a block of first output values by scaling the block to obtain scaled input values, performing a scaled one-dimensional (1D) transform on each row of the block, and performing a scaled 1D transform on each column of the block; and (2) performing a second transform on a block of second input values to obtain a block of second output values by performing a scaled 1D transform on each row of the block, performing a scaled 1D transform on each column of the block, and scaling the block.

Abstract: Techniques are described for encoding an audio video stream that is transmitted over a network, for example a wireless or IP network, such that an entire frame of audio and an entire frame of video are transmitted simultaneously within a period required to render the audio video stream frames by an application in a receiver. Aspects of the techniques include receiving audio and video RTP streams and assigning an entire frame of RTP video data to communication channel packets that occupy the same period, or less, as the video frame rate. Also an entire frame of RTP audio data is assigned to communication channel packets that occupy the same period, or less, as the audio frame rate. The video and audio communication channel packets are transmitted simultaneously. Receiving and assigning RTP streams can be performed in a remote station, or a base station.

Abstract: Methods and apparatus are described for improving the transmission of information over wireless communication channels. These techniques include determining available communication channels for transmitting information and determining possible physical layer packet sizes of the available channels. An information unit is partitioned into portions wherein the size of the portions are selected so as to match one of the physical layer packet sizes of the available communication channels. Another aspect is partitioning the information into a number of slices that correspond to the number of transmissions that occur during the information unit interval and assigning each partition to a corresponding transmission. The techniques can be used for various types of information, such as multimedia data, variable bit rate data streams, video data, or audio data.

Abstract: Certain aspects of the present disclosure relate to a method for quantizing signals and reconstructing signals, and/or encoding or decoding data for storage or transmission. Points of a signal may be determined as local extrema or points where an absolute rise of the signal is greater than a threshold. The tread and value of the points may be quantized, and certain of the quantizations may be discarded before the quantizations are transmitted. After being received, the signal may be reconstructed from the quantizations using an iterative process.

Abstract: Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications.

Abstract: Certain aspects of the present disclosure relate to techniques for low-complexity encoding (compression) of broad class of signals, which are typically not well modeled as sparse signals in either time-domain or frequency-domain. First, the signal can be split in time-segments that may be either sparse in time domain or sparse in frequency domain, for example by using absolute second order differential operator on the input signal. Next, different encoding strategies can be applied for each of these time-segments depending in which domain the sparsity is present.

Abstract: A method of using spiking neural network delays to represent sequences includes assigning one or more symbol neurons to each symbol in a dictionary. The method also includes assigning a synapse from each symbol neuron in a group to a particular ngram neuron. A set of synapses associated with the group of symbol neurons comprises a bundle of synapses. In addition, the method includes assigning a delay to each synapse in the bundle. The method further includes representing a symbol sequence based on sequential spiking of symbol neurons and ngram neuron spikes in response to detecting inter event intervals.

Abstract: Certain aspects of the present disclosure relate to techniques for low-complexity encoding (compression) of broad class of signals, which are typically not well modeled as sparse signals in either time-domain or frequency-domain. First, the signal can be split in time-segments that may be either sparse in time domain or sparse in frequency domain, for example by using absolute second order differential operator on the input signal. Next, different encoding strategies can be applied for each of these time-segments depending in which domain the sparsity is present.

Abstract: A method and system for resynchronizing an embedded multimedia system using bytes consumed in an audio decoder. The bytes consumed provides a mechanism to compensate for bit error handling and correction in a system that does not require re-transmission. The audio decoder keeps track of the bytes consumed and periodically reports the bytes consumed. A host microprocessor indexes the actual bytes consumed since bit errors may have been handled or corrected to a predetermined byte count to determine whether resynchronization is necessary.

Abstract: Certain aspects of the present disclosure relate to a method for quantizing signals and reconstructing signals, and/or encoding or decoding data for storage or transmission. Points of a signal may be determined as local extrema or points where an absolute rise of the signal is greater than a threshold. The tread and value of the points may be quantized, and certain of the quantizations may be discarded before the quantizations are transmitted. After being received, the signal may be reconstructed from the quantizations using an iterative process.

Abstract: Certain aspects of the present disclosure relate to techniques for low-complexity encoding (compression) of broad class of signals, which are typically not well modeled as sparse signals in either time-domain or frequency-domain. First, the signal can be split in time-segments that may be either sparse in time domain or sparse in frequency domain, for example by using absolute second order differential operator on the input signal. Next, different encoding strategies can be applied for each of these time-segments depending in which domain the sparsity is present.

Abstract: The present disclosure relates to a device and method for acquiring and processing sensor signals on a host device. The device comprises a jack and connects to a socket on the host device. The device further comprises an instrumentation block which draws power from the host socket to power its operation. The instrumentation block further processes signals and conveys this information to the host device up on connecting the device jack to the host socket. The host device controls certain aspects of the electronics module for acquiring and processing plurality of signals. The instrumentation block in the device connects to one or more sensors through cables to sense at least one of electrocardiogram (ECG), Electroencephalography (EEG), motion, airflow of respiratory system, body temperature, light intensity of arterial oxygen saturation level, blood pressure and any other physiology signal.

Abstract: Methods and apparatus are described for transmitting information units over a plurality of constant bit rate communication channel. The techniques include encoding the information units, thereby creating a plurality of data packets. The encoding is constrained such that the data packet sizes match physical layer packet sizes of the communication channel. The information units may include a variable bit rate data stream, multimedia data, video data, and audio data. The communication channels include CMDA channels, WCDMA, GSM channels, GPRS channels, and EDGE channels.

Abstract: Certain aspects of the present disclosure relate to a method for quantizing signals and reconstructing signals, and/or encoding or decoding data for storage or transmission. Points of a signal may be determined as local extrema or points where an absolute rise of the signal is greater than a threshold. The tread and value of the points may be quantized, and certain of the quantizations may be discarded before the quantizations are transmitted. After being received, the signal may be reconstructed from the quantizations using an iterative process.

Abstract: Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications.

Abstract: Methods and apparatus are described for improving the transmission of information over wireless communication channels. These techniques include determining available communication channels for transmitting information and determining possible physical layer packet sizes of the available channels. An information unit is partitioned into portions wherein the size of the portions are selected so as to match one of the physical layer packet sizes of the available communication channels. Another aspect is partitioning the information into a number of slices that correspond to the number of transmissions that occur during the information unit interval and assigning each partition to a corresponding transmission. The techniques can be used for various types of information, such as multimedia data, variable bit rate data streams, video data, or audio data.

Abstract: Low latency and computationally efficient techniques may be employed to account for errors in data such as low bit-width, oversampled data. In some aspects these techniques may be employed to mitigate audio artifacts associated with sigma-delta modulated audio data. In some aspects an error may be detected in a set of encoded data based on an outcome of a channel decoding process. Upon determining that a set of data may contain at least one error, the set of data may be replaced with another set of data that is based on one or more neighboring data sets. For example, in some aspects a set of data including at least one bit in error may be replaced with data that is generated by applying a cross-fading operation to neighboring data sets. In some aspects a given data bit may be flipped as a result of a linear prediction operation that is applied to PCM equivalent data that is associated with the given data bit and its neighboring data bits.

Abstract: Methods and apparatus are described for improving the transmission of information over wireless communication channels. These techniques include determining available communication channels for transmitting information and determining possible physical layer packet sizes of the available channels. An information unit is partitioned into portions wherein the size of the portions are selected so as to match one of the physical layer packet sizes of the available communication channels. Another aspect is partitioning the information into a number of slices that correspond to the number of transmissions that occur during the information unit interval and assigning each partition to a corresponding transmission. The techniques can be used for various types of information, such as multimedia data, variable bit rate data streams, video data, or audio data.

Abstract: Techniques for efficiently performing full and scaled transforms on data received via full and scaled interfaces, respectively, are described. A full transform is a transform that implements the complete mathematical description of the transform. A full transform operates on or provides full transform coefficients. A scaled transform is a transform that operates on or provides scaled transform coefficients, which are scaled versions of the full transform coefficients. The scaled transform may have lower computational complexity whereas the full transform may be simpler to use by applications. The full and scaled transforms may be for a 2D IDCT, which may be implemented in a separable manner with 1D IDCTs. The full and scaled transforms may also be for a 2D DCT, which may be implemented in a separable manner with 1D DCTs. The 1D IDCTs and 1D DCTs may be implemented in a computationally efficient manner.

Abstract: Methods and apparatus for audio and speech processing including generating a plurality of frames, each of the frames comprising a plurality of transform coefficients, and allocating bits to the transform coefficients in each of the frames such that at least two of the transform coefficients in the same frame have different bit allocations and the total number of the bits allocated to the transform coefficients in at least two of the frames is equal.