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:
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:
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:
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 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 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 wearable system including one or more wearable acquisition devices. Each acquisition device includes a sensor to capture samples of a biomedical signal and circuitry to process the samples for transmission to a mobile device. The samples are encoded for transmission and decoded at the mobile device to reconstruct the biomedical signal and, based on the reconstructed biomedical signal, provide output through a user interface of the mobile device. The wearable system includes at least an acquisition device for capturing an electro-cardiogram signal (ECG). Other biomedical signals, such as a photoplethysmograph (PPG) signal, may also be captured. The wearable system may comprise a Body Area Network (BAN).
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:
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.