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  Method and apparatus for removing quantization effects in a quantized signalRelated Patent Categories: Data Processing: Measuring, Calibrating, Or Testing, Measurement System In A Specific Environment, Electrical Signal Parameter Measurement System, Waveform Analysis, Frequency, Frequency SpectrumThe Patent Description & Claims data below is from USPTO Patent Application 20070179727. Brief Patent Description - Full Patent Description - Patent Application Claims
BACKGROUND [0001] 1. Field of the Invention [0002] The present invention relates to techniques for proactively detecting impending problems in computer systems. More specifically, the present invention relates to a method and an apparatus for removing quantization effects in a quantized signal which can be subsequently used to detect impending problems in a computer system. [0003] 2. Related Art [0004] Modern server computer systems are typically equipped with a significant number of sensors which monitor signals during the operation of the computer systems. Results from this monitoring process can be used to generate time series data for these signals which can subsequently be analyzed to determine how a computer system is operating. One particularly desirable application of this time series data is for purposes of "proactive fault monitoring" to identify leading indicators of component or system failures before the failures actually occur. [0005] Unfortunately, many of these computer systems use low-resolution eight-bit analog-to-digital (A/D) converters in all of their physical sensors to sample the signals. This causes readings of physical variables such as voltage, current, and temperature to be highly quantized. Hence, the sampled signal values from these sensors can only assume discrete values, and no readings can be reported between these discrete values. For example, voltages for system board components may be quantized to the nearest 10 mV; e.g. 1.60 V, 1.61 V, 1.62 V, etc. Hence, if the true voltage value is 1.6035 V, it can only be reported as one of the quantized values, 1.60 or 1.61. [0006] Note that the above-described quantization effects present a serious problem for proactive fault monitoring. Normally, one can apply statistical pattern recognition techniques to continuous signal values to detect if the signals start to drift away from steady-state values at a very early stage of system degradation. However, with significant quantization, conventional statistical pattern recognition techniques cannot be used effectively to detect the onset of subtle anomalies that might precede component or system failures. [0007] To overcome the drawbacks of the low-resolution quantized signals, researchers have used a technique called "burst sampling." Essentially, this technique restores high-resolution signals from low-resolution A/D converter outputs by removing the quantization effects. Specifically, a large "burst" of samples (typically hundreds of sample) are retrieved from low-level hardware registers of the server computer system being monitored. These samples are then collected through telemetry channels at the highest data rate that the hardware channels can support (typically at kHz rates). Next, the samples in the "burst" are averaged to obtain values that approximate signals sampled with high-resolution data-acquisition capability. [0008] Unfortunately, this burst sampling technique can be used only for a small subset of signals of interest in a large system. This is because the burst sampling creates a large burst demand for the bandwidth that is available for delivering telemetry samples via the system bus. In some large systems over 1000 telemetry signals are monitored concurrently. However, the burst sampling technique can consume the entire system bus bandwidth while delivering only a few tens of these signals. [0009] What is needed is a method and an apparatus that removes the quantization effects from low-resolution quantized signals without the above-described problems. SUMMARY [0010] One embodiment of the present invention provides a system that reconstructs a high-resolution signal from a set of low-resolution quantized samples. During operation, the system receives a time series containing low-resolution quantized signal values which are sampled from the high-resolution signal. Next, the system performs a spectral analysis on the time series to obtain a frequency series for the low-resolution quantized signal values. The system next selects a subset of frequency terms from the frequency series which have the largest amplitudes. The system then reconstructs the high-resolution signal by performing an inverse spectral analysis on the subset of the frequency terms. [0011] In a variation on this embodiment, the system selects the subset of the frequency terms by first sorting the frequency terms in the frequency series based on amplitudes of the frequency terms in the frequency series. [0012] In a variation on this embodiment, the spectral analysis is a Discrete Fourier Transform (DFT). [0013] In a variation on this embodiment, the inverse spectral analysis is an inverse Discrete Fourier Transform (IDFT). [0014] In a further variation on this embodiment, the DFT is computed using a Fast Fourier Transform (FFT). [0015] In a variation on this embodiment, the subset of the frequency terms is a predetermined number of frequency terms which have the largest amplitudes from the frequency series. [0016] In a further variation on this embodiment, the system precomputes the predetermined number. During this precomputation process, the system receives a high-resolution signal. Next, the system iteratively: selects the first n frequency terms which have the largest amplitudes from the frequency series; reconstructs a signal by performing an inverse spectral analysis on the selected n frequency terms; and computes a difference between the high-resolution signal and the reconstructed signal. The system then determines the predetermined number by identifying a value of n that gives rise to a minimum difference between the high-resolution signal and the reconstructed signal. [0017] In a further variation on this embodiment, the system computes the difference between the high-resolution signal and the reconstructed signal by computing a residual signal which is obtained by subtracting the reconstructed signal from the high-resolution signal. [0018] In a further variation on this embodiment, the amplitudes of the frequency series are determined by a power spectral density (PSD) of the frequency series. BRIEF DESCRIPTION OF THE FIGURES [0019] FIG. 1 illustrates a computer system with sensors that detect signals in different parts of the computer system in accordance with an embodiment of the present invention. [0020] FIG. 2 presents a flowchart illustrating a process of reconstructing a high-resolution signal from a set of low-resolution quantized samples in a computer system in accordance with an embodiment of the present invention. [0021] FIG. 3 presents a flowchart illustrating a process of precomputing the number for the selected subset of the frequency terms in accordance with an embodiment of the present invention. Continue reading... Full patent description for Method and apparatus for removing quantization effects in a quantized signal Brief Patent Description - Full Patent Description - Patent Application Claims Click on the above for other options relating to this Method and apparatus for removing quantization effects in a quantized signal patent application. ###  How KEYWORD MONITOR works... a FREE service from FreshPatents1. Sign up (takes 30 seconds). 2. Fill in the keywords to be monitored. 3. Each week you receive an email with patent applications related to your keywords. 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