Digital filtering for optimization of signals submerged in noise
Digital filtering for optimization of signals submerged in noise
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Digital filtering for optimization of signals submerged in noise
Post measurement synchronization of noise signals allowed for the investigation of previously unseen correlations. Noise of gamma, thermal and fast neutron signals performed similarly in estimating the prompt neutron decay constant at various subcritical states. The CPSD amplitude terms displayed different magnitudes. The neutron-based amplitudes suffered more from changes in detector efficiency as the number of fuel rods in the system increased. The time lag between 3 He tubes is observable using the CPSD phase angle and agreed with a simplified diffusion estimation.
The possibility of detecting artificial signals transmitted by alien civilizations via collimated X-ray or gamma-ray beams is investigated. The prospect of using such beams for human communication within the solar system and beyond is also discussed. Detector responses were simulated for input signals and analyzed using relative entropy. For simplicity, all signals were assumed to use on-off keying (OOK) modulation. “Real” signals were generated by taking digital files and sequentially feeding their raw binary data to the detector simulator, the resulting normalized information content of the detector signals was plotted and compared to random noise signals. Since jpeg files contain compressed information, these served as a proxy for artificial alien signals. This showed that there is a clear difference in measured information content between natural and artificial signals, even with relatively poor time resolution in the detector causing the signals to be smeared (dead-time/rise-time intervals many times longer than the duration between signal pulses). It was found that so long as the signal lasts for at least several rise-time/dead-time intervals, the distinction between random and artificial signals is obvious. A space-telescope with high time resolution for searching for such signals is briefly described and its basic requirements are outlined.
An interface logic circuit permitting the transfer of information between two computers having asynchronous clocks is disclosed. The information transfer involves utilization of control signals (including request, return-response, ready) to generate properly timed data strobe signals. Noise problems are avoided because each control signal, upon receipt, is verified by at least two clock pulses at the receiving computer. If control signals are verified, a data strobe pulse is generated to accomplish a data transfer. Once initiated, the data strobe signal is properly completed independently of signal disturbances in the control signal initiating the data strobe signal. Completion of the data strobe signal is announced by automatic turn-off of a return-response control signal.
Measurements have been made of coherence and phase spectra for the acoustic field in a subsonic wind tunnel. The data are interpreted in terms of simple analytical models for propagating and diffuse noise fields, including the presence of uncorrelated noise signals. It is found that low frequency noise propagates upstream and downstream from the fan, with the noise in the test section arriving in the upstream direction. High frequency sound is generated in the test section and propagates upstream and downstream. In the low frequency range, the ratio of diffuse to propagating energy is about eight for all locations in the test section, diffuser, and settling chamber; the value of the ratio increases with frequency.
Measurements have been made of coherence and phase spectra for the acoustic field in a subsonic wind tunnel. The data are interpreted in terms of simple analytical models for propagating and diffuse noise fields, including the presence of uncorrelated noise signals. It is found that low frequency noise propagates upstream and downstream from the fan, with the noise in the test section arriving in the upstream direction. High frequency sound appears to be generated in the test section and propagates upstream and downstream. In the low frequency range, the ratio of diffuse to propagating energy is about 8 for all locations in the test section, diffuser, and settling chamber; the value of the ratio increases with frequency. Further analysis is required to describe in better detail the effects of reverberation and incoherent sources in a duct-like environment.
An alternative to an optimal method of automated classification of signals modulated with M-ary phase-shift-keying (M-ary PSK or MPSK) has been derived. The alternative method is approximate, but it offers nearly optimal performance and entails much less complexity, which translates to much less computation time. Modulation classification is becoming increasingly important in radio-communication systems that utilize multiple data modulation schemes and include software-defined or software-controlled receivers. Such a receiver may "know" little a priori about an incoming signal but may be required to correctly classify its data rate, modulation type, and forward error-correction code before properly configuring itself to acquire and track the symbol timing, carrier frequency, and phase, and ultimately produce decoded bits. Modulation classification has long been an important component of military interception of initially unknown radio signals transmitted by adversaries. Modulation classification may also be useful for enabling cellular telephones to automatically recognize different signal types and configure themselves accordingly. The concept of modulation classification as outlined in the preceding paragraph is quite general. However, at the present early stage of development, and for the purpose of describing the present alternative method, the term "modulation classification" or simply "classification" signifies, more specifically, a distinction between M-ary and M'-ary PSK, where M and M' represent two different integer multiples of 2. Both the prior optimal method and the present alternative method require the acquisition of magnitude and phase values of a number (N) of consecutive baseband samples of the incoming signal + noise. The prior optimal method is based on a maximum- likelihood (ML) classification rule that requires a calculation of likelihood functions for the M and M' hypotheses: Each likelihood function is an integral, over a full cycle of carrier phase, of a complicated sum of functions of the baseband sample values, the carrier phase, the carrier-signal and noise magnitudes, and M or M'. Then the likelihood ratio, defined as the ratio between the likelihood functions, is computed, leading to the choice of whichever hypothesis - M or M'- is more likely. In the alternative method, the integral in each likelihood function is approximated by a sum over values of the integrand sampled at a number, 1, of equally spaced values of carrier phase. Used in this way, 1 is a parameter that can be adjusted to trade computational complexity against the probability of misclassification. In the limit as 1 approaches infinity, one obtains the integral form of the likelihood function and thus recovers the ML classification. The present approximate method has been tested in comparison with the ML method by means of computational simulations. The results of the simulations have shown that the performance (as quantified by probability of misclassification) of the approximate method is nearly indistinguishable from that of the ML method (see figure).
A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.
Assembly of commercial and custom-made electronic equipment designed to generate noisy intermediate-frequency or baseband received phase-modulation data-communication signals with accurately known signal-to-noise ratios. Signals used to perform signal-to-noise-ratio calibrations and other tests of responses of data-communication receivers to noisy incoming signals. Underlying principle applicable to generation of test signals for other advanced data-communication receivers.
One atmospheric variable which can be deduced from stratosphere-troposphere (ST) radar data other than wind speed and direction is C sub n sup 2, related to the eddy dissipation rate. The computation of C sub n sup 2 makes use of the transmitted power (average, or peak plus duty cycle), the range of the echoes, and the returned power. The returned power can be calibrated only if a noise source of known strength is imposed; e.g., in the absence of absolute calibration, one can compare the diurnal noise signal with the galactic sky temperature. Thus to compute C sub n sup 2 one needs the transmitter power, the returned signal as a function of height, and the returned noise at an altitude so high that it is not contaminated by any signal. Now C sub n sup 2 relates with the amount of energy within the inertial subrange, and for many research studies it may be desirable to relate this with background flow as well as shears or irregularities on the size of the sample volume. The latter are quantified by the spectral width.
Saccadic eye movements during search for a target embedded in noise are suboptimally guided by information about target location. Our goal is to compare the spatial information used to guide the saccades with that used for the perceptual decision. Three observers were asked to determine the location of a bright disk (diameter = 21 min) in white noise (signal-to-noise ratio = 4.2) from among 10 possible locations evenly spaced at 5.9 deg eccentricity. In the first of four conditions, observers used natural eye movements. In the three remaining conditions, observers fixated a central cross at all times. The fixation conditions consisted of three different presentation times (100, 200, 300 msec), each followed by a mask. Eye-position data were collected, with a resolution of (approximately) 0.2 deg. In the natural viewing condition, we measured. the accuracy with respect to the target and the latency of the first saccade. In the fixation conditions, we discarded trials in which observers broke fixation. Perceptual performance was computed for all conditions. Averaged across observers, the first saccade was correct (closest to the target location) for 56 +/- (SD) % of trials (chance = 10 %) and occurred after a latency of 313 +/- 56 msec. Perceptual performance averaged 53 +/- 4, 63 +/- 4, 65 +/- 2 % correct at 100, 200, and 300 msec, respectively. For the signal-to-noise ratio used, at the time of initiation of the first saccade, there is little difference between the amount of information about target location available to the perceptual and saccadic systems.
Minimizing a Euclidean distance in the complex plane optimizes a wide class of correlation metrics for filters implemented on realistic devices. The algorithm searches over no more than two real scalars (gain and phase). It unifies a variety of previous solutions for special cases (e.g., a maximum signal-to-noise ratio with colored noise and a real filter and a maximum correlation intensity with no noise and a coupled filter). It extends optimal partial information filter theory to arbitrary spatial light modulators (fully complex, coupled, discrete, finite contrast ratio, and so forth), additive input noise (white or colored), spatially nonuniform filter modulators, and additive correlation detection noise (including signal dependent noise).
We present an overview of the recent progress made in the development of a far-IR array of ultrasensitive hot-electronnanobolometers (nano-HEB) made from thin titanium (Ti) films. We studied electrical noise, signal and noisebandwidth, single-photon detection, optical noise equivalent power (NEP), and a microwave SQUID (MSQUID) basedfrequency domain multiplexing (FDM) scheme. The obtained results demonstrate the very low electrical NEP down to1.5x10-(sup 2)? W/Hz(sup 1)/(sup 2) at 50 mK determined by the dominating phonon noise. The NEP increases with temperature as ~ T(sup 3)reaching ~ 10-(sup 1)? W/Hz(sup 1)/(sup 2) at the device critical temperature TC = 330-360 mK. Optical NEP = 8.6x10-(sup 1)? W/Hz(sup 1)/(sup 2) at 357mK and 1.4x10-(sup 1)? W/Hz(sup 1)/(sup 2) at 100 mK respectively, agree with thermal and electrical data. The optical couplingefficiency provided by a planar antenna was greater than 50%. Single 8-?m photons have been detected for the first timeusing a nano-HEB operating at 50-200 mK thus demonstrating a potential of these detectors for future photon-countingapplications in mid-IR and far-IR. In order to accommodate the relatively high detector speed (~ ?s at 300 mK, ~ 100 ?sat 100 mK), an MSQUID based FDM multiplexed readout with GHz carrier frequencies has been built. Both the readoutnoise ~ 2 pA/Hz(sup 1)/(sup 2) and the bandwidth > 150 kHz are suitable for nano-HEB detectors.
Filtering optimization prior to limiting digital signals in strong noise, detailing bandwidth choice of single pole low pass filter
Electromagnetic interference, particularly from sources such as light fixtures and power supplies, negatively affects the function and performance of electronic systems. This noise, often quasi-periodic in nature, contains harmonic structure that can be used for noise estimation and suppression. This work proposes a novel method for tracking and filtering such noise signals that reduces the comb filter bandwidth required for noise estimation and suppression by tracking the instantaneous frequency of the fundamental component.
In support of the on-going automation of the Deep Space Network (DSN) a new method of generating analog test signals with accurate signal-to-noise ratio (SNR) is described. High accuracy is obtained by simultaneous generation of digital noise and signal spectra at the desired bandwidth (base-band or bandpass). The digital synthesis provides a test signal embedded in noise with the statistical properties of a stationary random process. Accuracy is dependent on test integration time and limited only by the system quantization noise (0.02 dB). The monitor and control as well as signal-processing programs reside in a personal computer (PC). Commands are transmitted to properly configure the specially designed high-speed digital hardware. The prototype can generate either two data channels modulated or not on a subcarrier, or one QPSK channel, or a residual carrier with one biphase data channel. The analog spectrum generated is on the DC to 10 MHz frequency range. These spectra may be up-converted to any desired frequency without loss on the characteristics of the SNR provided. Test results are presented.
Here, this study revisits the three-point sampling of the simplified Butler-Volmer equation to address the limitations of strong potentiodynamic polarization, which can introduce irreversible damage and uncertainty in corrosion analysis. The method extracts electrochemical kinetic parameters while minimizing polarization effects, evaluates noise sensitivity relative to overpotential, and accounts for errors from signal noise, OCP drift, ohmic resistance, and mass-transfer constraints. Verified against the Tafel extrapolation method for aluminum corrosion across a wide pH range, this low-polarization approach enables accurate evaluations with specific error estimates, offering a robust alternative to linear polarization resistance methods that assume constant Tafel slopes.
Vibrating columns of fluid used to calibrate transducers. Dynamic pressure calibration standard developed for calibrating flush diaphragm-mounted pressure transducers. Pressures up to 20 kPa (3 psi) accurately generated over frequency range of 50 to 1,800 Hz. System includes two conically shaped aluminum columns one 5 cm (2 in.) high for low pressures and another 11 cm (4.3 in.) high for higher pressures, each filled with viscous fluid. Each column mounted on armature of vibration exciter, which imparts sinusoidally varying acceleration to fluid column. Signal noise low, and waveform highly dependent on quality of drive signal in vibration exciter.