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Topic: Signal reconstruction

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	Method of performing signal reconstruction at the receiving end of a communications system, such as for GSM - US ... (Site not responding. Last check: 2007-10-08)
		Typically, the known portion of the transmitted signal burst is received at the receiving end of the communications system, along with the unknown portion, and the known portion may then be employed to obtain an estimate of the communications channel for further signal processing of the unknown portion of the signal burst.
		Once the first discrete signal is reconstructed, the second discrete signal may be reconstructed using the first reconstructed discrete signal by, for example, performing a read from memory, in comparison with reading the entire channel estimate, such as for a hardware implementation of the conventional approach, as previously described.
		Once the first discrete signal is reconstructed from the discrete channel tap components of the estimate of the communications channel, the second discrete signal may be reconstructed from the first reconstructed discrete signal and one of the discrete channel tap components, as explained in more detail hereinafter.
	www.patentstorm.us /patents/5592514.html (6366 words)

	Signal reconstruction - Wikipedia, the free encyclopedia
		In signal processing, reconstruction usually means the determination of an original continuous signal from a sequence of equally spaced samples.
		This fact that the dimensions have to agree is related to the Nyquist-Shannon sampling theorem.
		Of course, one can choose some reconstruction formula first, then either compute some sampling algorithm from the reconstruction formula, or analyze the behavior of a given sampling algorithm with respect to the given formula.
	en.wikipedia.org /wiki/Signal_reconstruction (302 words)

	Signal reconstruction from regularly sampled data
		The DFT of the regularly sampled signal is plotted in Figure 2 b in magenta superimposed to the Fourier transform of the original signal in blue.
		In the case of N=9 the Nyquist condition is respected and the signal is reconstructed perfectly as shown in Figure 3.
		In the case the number of samples is lowered and therefore the sampling interval increases, the reconstruction is imperfect as shown from the examples in Figure 4 a for N=8 and Figure 4 b for N=6.
	homepages.inf.ed.ac.uk /rbf/CVonline/LOCAL_COPIES/PIRODDI1/NUFT/node6.html (363 words)

	Frequency domain signal reconstruction compensating for phase adjustments to a sampling signal - Patent 5793801 (Site not responding. Last check: 2007-10-08)
		A signal transmitted from the transceiver is input to the digital filter and delayed for a plurality of delay stages to generate a series of input signals.
		Because the present invention reconstructs a received signal from signal samples taking into account aliased frequency components, the fact that a signal is no longer sampled at greater than twice the highest frequency component of received signal it does not undermine the accuracy of the reconstructed signal.
		In general, the gain applied to the input signal is adapted by comparison of the input signal to fixed amplitude thresholds and increasing or decreasing the gain as necessary to achieve the amplitudes standardized for symbols -3, -1, +1, and +3.
	www.freepatentsonline.com /5793801.html (8573 words)

	criticism
		The perfect reconstruction of the signal lies in the elimination of these three distortion such that the reconstructed signal becomes the exact replica of the original.
		The reconstruction of the signal can be achieved either by retaining odd components or even components of in each of the analysis filter output.
		Aliasing term in the perfect reconstruction theory of 2-channel filter bank is a fictitious term, it does not occur because of the down sampling and hence we need not concern for it.
	www.geocities.com /kiranisingh/Filterbank/criticism.htm (1469 words)

	Sampled Signal Reconstruction in Tcl driven Maxima
		In this example tcl is used to fabricate formulas for maxima's interpreter, for a part of one of the most important issues in signal processing and computerized real-world data interaction: the reconstruction of a sampled signal.
		Which gives all the terms for 28 samples reconstructing a signal made by adding three sine components of a square wave approximation with cycle length 28, sampled at equidistant times [0,1,2...28], where each sample is weighing a sinc function for continuous signal reconstruction.
		An important concept for computer represented signals or changing variables which are in fact continuous, is how a signal develops with time, such as I examplified with snack in Sound envelope generator.
	wiki.tcl.tk /11991 (631 words)

	Signal Sampling & Reconstruction
		This signal modulates the value of the least significant bit and produces a pulse width modulation signal, where the duty cycle of the pulse (percentage of the time the pulse is high) is proportional to the value of the voltage level above the lowest quantisation levels divided by the resolution (i.e.
		When the signal is later reconstructed using a lowpass filter after the digital to analogue converter (DAC), the filter integrates (adds the contributions of) this pulse width modulation signal to reproduce values closer to the original analogue sample values.
		To reconstruct the analogue signal that was sampled by the ADC and encoded as a sequence of PCM numbers, a digital to analogue converter (DAC) is used in conjunction with a lowpass filter.
	www.digitalradiotech.co.uk /sampling.htm (1085 words)

	System and method for radio signal reconstruction using signal processor - Patent 5864754
		The device of claim 6, wherein the DSP outputs a gain adjust signal to the controller when the rf signal input to the DSP is characterized by an amplitude outside of an amplitude range, and the controller dynamically establishes the gain factor based on the gain adjust signal.
		Preferably, the electromagnetic signal is an rf signal, and the device further includes a digital to analog converter (DAC) for converting the reconstructed rf signal to an analog reconstructed rf signal, prior to sending the reconstructed rf signal to the mixer circuit.
		While the disclosure herein focusses on rf waveform reconstruction, it is to be understood that the principles of the present invention apply equally to other forms of modulated electromagnetic waves that are modulated as appropriate for the data the waves represent.
	www.freepatentsonline.com /5864754.html (5230 words)

	Part I: Fourier Transforms and Sampling
		This section is concerned with: (1) the relationship between the time variation of a signal and its frequency spectrum, and (2) digital signals, such as music on a compact disk.
		There is exactly the same kind of relationship for sampled signals; the integral in equation (1b) is replaced by a summation, and the continuous times and frequencies are replaced by discrete values.
		The convolution theorem also proves that a signal that is finite in time has an infinite spectrum: the response can always be expressed as a convolution with a sinc function, which extends the spectrum to infinity.
	www.silcom.com /~aludwig/Signal_processing/Signal_processing.htm (2731 words)

	Image Interpolation for Scaling (Site not responding. Last check: 2007-10-08)
		To begin, let's consider the 1D case of a signal (call it f) that we would like to dialate (expand in time) by a factor of 2 (call the resulting signal g).
		If we had the original signal that f was sampled from, we could sample the signal at all of the desired points.
		These reconstructions can be done using the same spike generation and reconstuction filter kernels as done in 1D, except that the kernels are now 2D.
	www.cs.wisc.edu /graphics/Courses/cs-638-1999/image_scaling.htm (1313 words)

	[No title] (Site not responding. Last check: 2007-10-08)
		These discrete signals are processed by digital signal processors, and the processed signals are converted into analog signals using a reconstruction operation (called digital-to-analog conversion or DAC).
		Reconstruction From the sampling theorem and the above examples it is clear that if we sample band-limited xa(t) above its Nyquist rate, then we can reconstruct xa(t) from its samples x(n).
		Reconstruct the analog signal ya(t) from the samples x(n) using the sinc interpolation (use (t = 0.001) and determine the frequency in ya(t) from your plot.
	gear.kku.ac.th /~nawapak/DSP/DSPLAB_03.doc (940 words)

	Signal Reconstruction - FDI Online Design Guide
		Roll-off need not be as sharp as an anti-alias prefilter, which must push the target system's useful bandwidth as close as possible to the Nyquist frequency.
		Even if the original signal bandwidth is 100% of Nyquist (an unrealizable goal without serious alias errors), the lowest undesirable frequency in the D/A output is the second harmonic.
		According to Fourier-transform mathematics, a waveform reconstructed using a first-order hold exhibits an amplitude error (E) that varies as a function of frequency f and the sampling frequency f
	www.freqdev.com /guide/sigrecon.html (299 words)

	[No title]
		The correct LFV spectrum (based on K=3 and bandwidth parameter p =2) evals-synth-1.out and the corresponding 2ndary and 3rd eigenvalue spectra evals-synth-2.out evals-synth-3.out are also provided for the synthetic dataset, as is the evolutive LFV spectrum evals-synth-40yrwin-1.out based on 40 year (480 month) moving window.
		To calculate the spatial pattern of a frequency-modulated signal, either the (1) the fixed-frequency pattern for a particular segment or (2) the average of several such fixed-frequency patterns for different segments of the full data series (ie, early, middle, late) should be calculated.
		This objective time-domain reconstruction is provided by determining finding the set of weights on the reconstructions (0)-(2) (adding to unity) which minimizes the misfit.
	pangea.stanford.edu /Oceans/GES290/Mann-SVD/README (810 words)

	Reconstruction of Periodic Sonar Signals Hidden in Wideband Noise Using Ensemble (Site not responding. Last check: 2007-10-08)
		The reconstruction task is particularly difficult when the signal is “hidden” in additive noise and the signal-to-noise ratio is poor.
		Spectral estimates are ensemble-averaged to enhance the signal power and reduce the residual spectral variance of the additive noise.
		In the reconstruction procedure, the noisy signal is reused to obtain one or more cycles of the “clean” signal.
	www.nadn.navy.mil /Users/ee/cameronc/Publications/ReconstructionofPeriodicSonarSignalsHiddeninWidebandNoiseUsingEnsemble.html (413 words)

	FDI DSP - Digital Signal Processing - Design Guide
		These signals are passed through structures that shift the clocked data into summers (adders), delay blocks and multipliers.
		Application specific solutions (programs) that require signal tracking or dynamically changing performance parameters are typically better suited for windowing since convergence is not a concern with windowing.
		A solution is to adjust the clock, which forces adjustments in the anti-alias and reconstruction filter, therefore requiring multiple fixed frequency or programmable filters (typically not cost effective).
	www.freqdev.com /guide/dspguide.html (3338 words)

	Criteria For Perfect Reconstructiblity
		We also discuss why perfect reconstruction is possible in the case of DB wavelets and some cases of filter banks on the basis of our newly found criteria.
		In the case of wavelets and filter coefficients, a signal is decomposed into an approximation and a detail component using two decomposition filters.
		When a signal is decomposed into two or more levels, then the reconstruction formulas are used repeatedly beginning reconstruction from the components decomposed last.
	www.geocities.com /kiranisingh/criteria.html (3251 words)

	Representation of Acoustic Communication Signals by Insect Auditory Receptor Neurons -- Machens et al. 21 (9): 3215 -- ...
		As shown by this example, stimulus reconstruction does not aim at recovering the original, complete physical stimulus w(t) but instead requires the identification of a representation of the stimulus that is relevant for the animal, in the present case the AM signal s(t).
		Reconstruction of an LMD signal with 50 Hz cut-off frequency from the responses of a single receptor.
		The estimated signal is obtained by a convolution of the spike train with this filter, which amounts to replacing each spike by the filter function.
	www.jneurosci.org /cgi/content/full/21/9/3215 (8814 words)

	High Resolution Signal Reconstruction
		In high resolution speech reconstruction, we attempt to reconstruct the fine detail of the log energy spectrum of short overlapping segments of speech.
		The blue dotted line is the estimate of clean speech produced by the algorithm, and the light blue shaded area shows the first standard deviation of the estimate, indicating the relative confidence in the estimate.
		Notice that the confidence of the estimate is lower in the harmonic valleys, where the signal to noise ratio is low.
	research.microsoft.com /users/traustik/MSR_HRSR.htm (218 words)

	Systat Software Inc. - AutoSignal - HTML Help
		In addition to the data, the reconstruction can optionally consist of the eigenvectors, the principal components, the data components, FFTs of the data components, an FFT of the data, AR spectra of the components, or an AR spectrum of the data.
		The Wavelet Filtering and Reconstruction option offers the means to reconstruct signals from spectral components that have been isolated in the time-frequency domain.
		The Fourier Interpolation option is similar to the Fourier Filtering and Reconstruction option except that the reconstruction is computed directly from the amplitude, frequency, and phase of the sine components rather than by an inverse FFT.
	www.systat.com /products/AutoSignal/help?sec=1193 (530 words)

	Efficient Methods for Digital Signal and Image Reconstruction from Nonuniform Samples (Site not responding. Last check: 2007-10-08)
		Digital signal reconstruction and image reconstruction refers to a class of problems which are among the most fundamental in the realm of science.
		In this report we concentrate on the reconstruction of a one- or two-dimensional signal from nonuniform spaced samples.
		In many of these problems the measured signal or image is band-limited or can be approximated sufficiently precise by a band-limited function.
	www.mat.univie.ac.at /~nuhag/papers/1993/str1193.html (386 words)

	Selection of Observations in Signal Reconstruction - Reeves, Heck (ResearchIndex) (Site not responding. Last check: 2007-10-08)
		Abstract: In some signal reconstruction problems, the observation equations can be used as a priori information for selecting the best combination of observations before acquiring them.
		Introduction Signal reconstruction uses measurements in one domain to estimate...
		Assumed Signal Statistics The distribution of orthogonal components of the signal and error terms may be analyzed by expanding the m...
	citeseer.ist.psu.edu /reeves95selection.html (504 words)

	Mathematics for Multimedia Signal Processing II Discrete Finite Frames and Signal Reconstruction - Ferreira ... (Site not responding. Last check: 2007-10-08)
		Abstract: Certain signal reconstruction problems can be understood in terms of frames and redundant representations.
		The redundancy is useful because it leads to robust signal representations, that is, representations in which partial loss of data can be tolerated without misbehavior or adverse effects.
		Ferreira, "Mathematics for multimedia signal processing II---Discrete finite frames and signal reconstruction," in Signal Processing for Multimedia, J. Byrnes, Ed.
	citeseer.ist.psu.edu /ferreira99mathematics.html (804 words)

	Paulo J. S. G. Ferreira
		No assumptions are made regarding the distribution of the missing samples, in contrast with the often studied extrapolation problem, in which the known samples are grouped together: the observed signal is regarded as a sampled version of the original, and the reconstruction result can be seen as a sampling result.
		Explicit best-possible upper and lower bounds for the error as a function of the number of iterations, and the signals for which the bounds are attained.
		For low-pass signals the best convergence rates are obtained when the distances among the missing samples are a multiple of a certain integer.
	www.ieeta.pt /~pjf/t_subject_frames.html (907 words)

	Information Systems Technology (Site not responding. Last check: 2007-10-08)
		Iterative algorithms for signal reconstruction from partial time- and frequency-domain knowledge have proven useful in a number of application areas.
		In this paper, a general convergence proof, applicable to a general class of such iterative reconstruction algorithms, is presented.
		Two examples studied in detail are time-limited extrapolation (equivalently, band-limited extrapolation) and phase-only signal reconstruction.
	www.ll.mit.edu /SST/pubs/convergence-tfq-abs.html (171 words)

	The Sampling Theorem and signal reconstruction
		For a signal whose duration is T this means that we can represent all of the signal information by measuring the signal level at 2N +1 points equally spaced along the signal waveform.
		These samples can later be used to reconstruct all of the details of the original signal — even recovering details of the actual signal pattern ‘in between’ the sampled moments.
		It is important to realise that, under these circumstances, the recovered waveform is not a ‘guess' but a reliable reconstruction of what we would have observed if the original signal had been measured at these other moments.
	www.st-andrews.ac.uk /~jcgl/Scots_Guide/iandm/part7/page3.html (1182 words)

	ICASSP-99 -> Technical Program -> Technical Sessions
		In digital IQ modulators generating Continuous Phase Frequency Shift Keying (CPFSK) signals, departures from flat-magnitude, linear phase in the pass bands of signal reconstruction filters in the I and Q channels cause ripple in the output signal envelope.
		First, we address the uniqueness and reconstruction of a two-dimensional signal from the Fourier intensities of the three signals: the original signal, the signal windowed by a window w(m,n), and the signal winowed by its complementary window wc(m,n)= 1-w(m,n).
		This paper presents a new paradigm for signal reconstruction and superresolution, Correlation Kernel Analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class-specific basis functions.
	www.eas.asu.edu /~icassp99/technical/sessions/abstracts-SPTM-14.html (1105 words)

	Analog signal metrology for mixed signal ICs
		Signal reconstruction reconstructs a multiple period low-rate sampled waveform into a one-period high-rate sampled waveform.
		With which, we are able to provide sufficient samples of analog signals for DSP based testing using on-chip ADCs.
		Test results show that a 128-sample-per-period waveform can be reconstructed from a 2.4 samples per period waveform sampled by a 20 MHz 8-bit ADC.
	csdl2.computer.org /persagen/DLAbsToc.jsp?resourcePath=/dl/proceedings/&toc=comp/proceedings/ats/1997/8209/00/8209toc.xml&DOI=10.1109/ATS.1997.643958 (153 words)

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