Showing papers on "Noise measurement published in 2004"

CMOS low-noise amplifier design optimization techniques

Abstract: This paper reviews and analyzes four reported low-noise amplifier (LNA) design techniques applied to the cascode topology based on CMOS technology: classical noise matching, simultaneous noise and input matching (SNIM), power-constrained noise optimization, and power-constrained simultaneous noise and input matching (PCSNIM) techniques. Very simple and insightful sets of noise parameter expressions are newly introduced for the SNIM and PCSNIM techniques. Based on the noise parameter equations, this paper provides clear understanding of the design principles, fundamental limitations, and advantages of the four reported LNA design techniques so that the designers can get the overall LNA design perspective. As a demonstration for the proposed design principle of the PCSNIM technique, a very low-power folded-cascode LNA is implemented based on 0.25-/spl mu/m CMOS technology for 900-MHz Zigbee applications. Measurement results show the noise figure of 1.35 dB, power gain of 12 dB, and input third-order intermodulation product of -4dBm while dissipating 1.6 mA from a 1.25-V supply (0.7 mA for the input NMOS transistor only). The overall behavior of the implemented LNA shows good agreement with theoretical predictions.

Modified derivative superposition method for linearizing FET low noise amplifiers

Abstract: Intermodulation distortion in field-effect transistors (FETs) at RF frequencies is analyzed using the Volterra-series analysis. The degrading effect of the circuit reactances on the maximum IIP3 in the conventional derivative-superposition (DS) method is explained. The noise performance of this method is also analyzed and the effect of the subthreshold biasing of one of the FETs on the noise figure (NF) is shown. A modified DS method is proposed to increase the maximum IIP3 at RF. It was used in a 0.25-mum Si CMOS low-noise amplifier (LNA) designed for cellular code-division multiple-access receivers. The LNA achieved +22-dBm IIP3 with 15.5-dB gain, 1.65-dB NF, and 9.3 mA@2.6-V power consumption

A method for modeling noise in medical images

Abstract: We have developed a method to study the statistical properties of the noise found in various medical images. The method is specifically designed for types of noise with uncorrelated fluctuations. Such signal fluctuations generally originate in the physical processes of imaging rather than in the tissue textures. Various types of noise (e.g., photon, electronics, and quantization) often contribute to degrade medical images; the overall noise is generally assumed to be additive with a zero-mean, constant-variance Gaussian distribution. However, statistical analysis suggests that the noise variance could be better modeled by a nonlinear function of the image intensity depending on external parameters related to the image acquisition protocol. We present a method to extract the relationship between an image intensity and the noise variance and to evaluate the corresponding parameters. The method was applied successfully to magnetic resonance images with different acquisition sequences and to several types of X-ray images.

On-die droop detector for analog sensing of power supply noise

Abstract: Understanding the supply fluctuations of various frequency harmonics is essential to maximizing microprocessor performance. Conventional methods used for analog validation of the power delivery system fall short in one or more of the following areas. 1) Measurement accuracy in both frequency and time domains, especially for very high-frequency noise caused by large di/dt events. The multigigahertz power supply noise attenuates very quickly away from the die. Conventional approaches of measuring the noise at the pins of the package or at the die using capacitive probes are not accurate for multigigahertz clocks. For this reason, the observability of high-frequency on-die noise has been very tricky. 2) Implementation (e.g., delivery) of analog references to multiple areas across a "noisy" die, compactness/modularity of the measurement units, restraining assumptions inherent in the measurement circuit such as periodicity of the supply noise event. 3) Automation to enable a timely volume of measurements. The efficiency of the measurements is key to correlating a particular speed path to poser supply noise. To address these issues, this paper presents an on-die droop detector (ODDD), a scalable IC solution implemented and validated on a 90-nm process, for analog sensing of differential high-bandwidth supply noise.

Challenges and Recent Developments in Hearing Aids: Part I. Speech Understanding in Noise, Microphone Technologies and Noise Reduction Algorithms

Abstract: This review discusses the challenges in hearing aid design and fitting and the recent developments in advanced signal processing technologies to meet these challenges. The first part of the review discusses the basic concepts and the building blocks of digital signal processing algorithms, namely, the signal detection and analysis unit, the decision rules, and the time constants involved in the execution of the decision. In addition, mechanisms and the differences in the implementation of various strategies used to reduce the negative effects of noise are discussed. These technologies include the microphone technologies that take advantage of the spatial differences between speech and noise and the noise reduction algorithms that take advantage of the spectral difference and temporal separation between speech and noise. The specific technologies discussed in this paper include first-order directional microphones, adaptive directional microphones, second-order directional microphones, microphone matching algorithms, array microphones, multichannel adaptive noise reduction algorithms, and synchrony detection noise reduction algorithms. Verification data for these technologies, if available, are also summarized.

Noise-dependent postfiltering

Abstract: The paper introduces a modification of the commonly used postfilter that improves performance when acoustic background noise is present. The modification consists of replacing the nonadaptive postfilter parameters that govern the degree of spectral emphasis (commonly denoted as /spl gamma//sub 1/ and /spl gamma//sub 2/) with parameters that adapt to the noise statistics. We describe an effective mapping from the noise statistics to the emphasis parameters and provide a low complexity noise estimation algorithm that is sufficient for this application. The resulting noise-adaptive postfilter successfully attenuates the background noise and naturally converges to the conventional postfilter at high SNR conditions. Thus, the speech enhancement problem is solved with minimal modification of legacy codecs, since the existing structure of the speech codec is used. Test results indicate that the presented algorithm significantly outperforms the standard postfilter with non-adaptive parameters.

Phase noise in digital frequency dividers

Abstract: This paper presents a physical derivation of phase noise in source-coupled-logic frequency dividers. This analysis takes into account both white and flicker noise sources and is verified on two 32/33 dual-modulus prescalers integrated in a 0.35-/spl mu/m CMOS process. Design techniques for high-speed and low-noise operation are provided. The two integrated prescalers are identical apart from a synchronizing flip-flop at the output of one of them. The measured phase spectra are in good agreement with the estimates and demonstrate that the final synchronization allows a better trade-off between noise and power consumption. The maximum operating frequency is 3 GHz, the power consumption is 27 mW and the phase noise floor is -163 dBc/Hz referred to the 78-MHz output.

Detail preserving impulsive noise removal

Abstract: Most image processing applications require noise elimination. For example, in applications where derivative operators are applied, any noise in the image can result in serious errors. Impulsive noise appears as a sprinkle of dark and bright spots. Transmission errors, corrupted pixel elements in the camera sensors, or faulty memory locations can cause impulsive noise. Linear filters fail to suppress impulsive noise. Thus, non-linear filters have been proposed. Windyga's peak-and-valley filter, introduced to remove impulsive noise, identifies noisy pixels and then replaces their values with the minimum or maximum value of their neighbors depending on the noise (dark or bright). Its main disadvantage is that it removes fine image details. In this work, a variation of the peak-and-valley filter is proposed to overcome this problem. It is based on a recursive minimum–maximum method, which replaces the noisy pixel with a value based on neighborhood information. This method preserves constant and edge areas even under high impulsive noise probability. Finally, a comparison study of the peak-and-valley filter, the median filter, and the proposed filter is carried-out using different types of images. The proposed filter outperforms other filters in the noise reduction and the image details preservation. However, it operates slightly slower than the peak-and-valley filter.

A sampling algorithm for digitally controlled boost PFC converters

Abstract: Digital control of a boost power factor correction (PFC) converter requires sampling of the input current. As the input current contains a considerable amount of switching ripple and high frequency switching noise, the choice of the sampling instant is very important. To avoid aliasing without employing a (very) high sampling frequency, the sampling is synchronized with the pulse width modulation (PWM). Sampling algorithms employing this technique successfully reject the input current ripple but are not immune to the high frequency switching noise present on all sampled signals. Therefore, a new sampling algorithm, called alternating-edge-sampling and intended for center-based or symmetric PWM, is deduced with as most important features: switching noise immunity, straightforwardness, accurate measurement of the averaged input current and the need for only few processor cycles. The operating principle, design issues and a theoretical study of the input current error induced by the sampling algorithm due to sampling instant timing errors are derived. All theoretical results are validated experimentally for a digitally controlled boost PFC converter switching at 50 kHz.

Adaptive alpha-trimmed mean filters under deviations from assumed noise model

Abstract: Alpha-trimmed mean filters are widely used for the restoration of signals and images corrupted by additive non-Gaussian noise. They are especially preferred if the underlying noise deviates from Gaussian with the impulsive noise components. The key design issue of these filters is to select its only parameter, /spl alpha/, optimally for a given noise type. In image restoration, adaptive filters utilize the flexibility of selecting /spl alpha/ according to some local noise statistics. In the present paper, we first review the existing adaptive alpha-trimmed mean filter schemes. We then analyze the performance of these filters when the underlying noise distribution deviates from the Gaussian and does not satisfy the assumptions such as symmetry. Specifically, the clipping effect and the mixed noise cases are analyzed. We also present a new adaptive alpha-trimmed filter implementation that detects the nonsymmetry points locally and applies alpha-trimmed mean filter that trims out the outlier pixels such as edges or impulsive noise according to this local decision. Comparisons of the speed and filtering performances under deviations from symmetry and Gaussian assumptions show that the proposed filter is a very good alternative to the existing schemes.

A novel EMI filter design method for switching power supplies

Abstract: This work introduces an improved and simplified method to design electromagnetic interference (EMI) filters for both dc-dc and ac-dc switching power supplies. This method uses the practical approach of measuring the power supply noise spectrum and using the data to calculate the maximum possible magnitude and minimum possible magnitude of the differential mode and common mode noise impedances. The noise impedance magnitude information aids the design of the EMI filter. Phase information for the noise impedance is not required. In addition, information about the topology and control method of the power supply is not needed. This method solves the limitations of existing EMI filter design methods, which are either too complicated to use, or are based on ideal cases that neglect the noise impedance. The analysis and experimental results show that this method can guarantee that the required attenuation can be achieved, especially at low frequencies.

Estimation of noise in a speech signal

Abstract: A speech communication or computing device comprises at least one speech input device for receiving noisy speech uttered by a speaker. A speech processing function comprises a voice recognition function, which comprises a noise reduction function ( 235 ) having a Wiener Filter ( 335 ) with adjustable filter co-efficients. The speech input device also comprises multiple microphones ( 142, 144 ) configured to provide a substantially continuous noise signal to a noise spectrum estimation function ( 325 ) of the noise reduction function ( 235 ) to provide a substantially continuous estimate of noise. The noise estimate is used to adjust the filter co-efficients of the Wiener Filter ( 335 ), thereby removing noise from the noisy speech. A microphone array and a method for speech recognition are also described. By using the noise estimate from, say, a microphone array, the Wiener filter coefficients can be updated substantially continuously, for example, each speech frame. This enables the noise to be tracked more closely than in known techniques. As the noise within a speech signal is tracked more closely, it can therefore be removed more effectively.

Training methods for image noise level estimation on wavelet components

Abstract: The estimation of the standard deviation of noise contaminating an image is a fundamental step in wavelet-based noise reduction techniques. The method widely used is based on the mean absolute deviation (MAD). This model-based method assumes specific characteristics of the noise-contaminated image component. Three novel and alternative methods for estimating the noise standard deviation are proposed in this work and compared with the MAD method. Two of these methods rely on a preliminary training stage in order to extract parameters which are then used in the application stage. The sets used for training and testing, 13 and 5 images, respectively, are fully disjoint. The third method assumes specific statistical distributions for image and noise components. Results showed the prevalence of the training-based methods for the images and the range of noise levels considered.

Multichannel post-filtering in nonstationary noise environments

Abstract: In this paper, we present a multichannel post-filtering approach for minimizing the log-spectral amplitude distortion in nonstationary noise environments. The beamformer is realistically assumed to have a steering error, a blocking matrix that is unable to block all of the desired signal components, and a noise canceller that is adapted to the pseudo-stationary noise but not modified during transient interferences. A mild assumption is made that a desired signal component is stronger at the beamformer output than at any reference noise signal, and a noise component is strongest at one of the reference signals. The ratio between the transient power at the beamformer output and the transient power at the reference noise signals is used to indicate whether such a transient is desired or interfering. Based on a Gaussian statistical model and combined with an appropriate spectral enhancement technique, we derive estimators for the signal presence probability, the noise power spectral density, and the clean signal. The proposed method is tested in various nonstationary noise environments. Compared with single-channel post-filtering, a significantly reduced level of nonstationary noise is achieved without further distorting the desired signal components.

Method and device for noise reduction

Abstract: The present invention is related to a method to reduce noise in a noisy speech signal, comprising the steps of - applying at least two versions of the noisy speech signal to a first filter. The first filter outputs a speech reference signal and at least one noise reference signal, - applying a filtering operation to each of the at least one noise reference signals, and - subtracting from the speech reference signal each of the filtered noise reference signals. The filtering operation is performed with filters having filter coefficients determined by taking into account speech leakage contributions in the at least one noise reference signal.

A new method for estimating the number of harmonic components in noise with application in high resolution radar

Abstract: In order to operate properly, the superresolution methods based on orthogonal subspace decomposition, such as multiple signal classification (MUSIC) or estimation of signal parameters by rotational invariance techniques (ESPRIT), need accurate estimation of the signal subspace dimension, that is, of the number of harmonic components that are superimposed and corrupted by noise. This estimation is particularly difficult when the S/N ratio is low and the statistical properties of the noise are unknown. Moreover, in some applications such as radar imagery, it is very important to avoid underestimation of the number of harmonic components which are associated to the target scattering centers. In this paper, we propose an effective method for the estimation of the signal subspace dimension which is able to operate against colored noise with performances superior to those exhibited by the classical information theoretic criteria of Akaike and Rissanen. The capabilities of the new method are demonstrated through computer simulations and it is proved that compared to three other methods it carries out the best trade-off from four points of view, S/N ratio in white noise, frequency band of colored noise, dynamic range of the harmonic component amplitudes, and computing time.

Fast calibration of high-order adaptive optics systems

Abstract: We present a new method of calibrating adaptive optics systems that greatly reduces the required calibration time or, equivalently, improves the signal-to-noise ratio. The method uses an optimized actuation scheme with Hadamard patterns and does not scale with the number of actuators for a given noise level in the wave-front sensor channels. It is therefore highly desirable for high-order systems and/or adaptive secondary systems on a telescope without a Gregorian focal plane. In the latter case, the measurement noise is increased by the effects of the turbulent atmosphere when one is calibrating on a natural guide star.

On the generalized DFIIt structure and its state-space realization in digital filter implementation

Abstract: It is well known that for a digital filter of order p, the number of nontrivial parameters in the classical optimal state-space realizations is proportional to p/sup 2/, while the traditional shift operator z-based direct-form II transposed (zDFIIt) structure, though having poor numerical properties, is one of the most efficient structures, just possessing 3p+1 nontrivial parameters. In this paper, based on the concept of polynomial operators, a new structure is proposed for digital filter implementation, which is a generalization of the traditional zDFIIt and the prevailing /spl delta/DFIIt structures. This structure, denoted as /spl rho/DFIIt, possesses 3p+1 nontrivial parameters plus p parameters at choice. Expressions for evaluating the sensitivity measure and the roundoff noise gain are derived for the /spl rho/DFIIt structure and its equivalent state-space realization that has the same structure complexity. It is shown that the state-space realization always yields a smaller roundoff noise gain than the /spl rho/DFIIt structure. One of the nice properties of these two structures is that for a given digital filter, they can be optimized with the p free parameters. The optimal structure problems can be solved with exhaustive researching under practical considerations. Numerical examples are presented to illustrate the design procedure.

Cepstral gain normalization for noise robust speech recognition

Abstract: The paper describes a robust speech recognition technique which normalizes cepstral gains in order to remove effects of additive noise. We assume that the effects can be expressed by an approximate model which consists of gain and DC components in log-spectrum. Accordingly, we propose cepstral gain normalization (CGN) which normalizes the gains by means of calculating maximum and minimum values of cepstral coefficients in speech frames. The proposed method can extract noise robust features without a priori knowledge and environmental adaptation because it is applied to both training and testing data. We have evaluated recognition performance under noisy environments using the Noisex-92 database and a 100 Japanese city names task. The CGN provides improvements of recognition accuracy at various SNRs compared with combinations of conventional methods.

A noise estimation algorithm with rapid adaptation for highly nonstationary environments

Abstract: A noise estimation algorithm is proposed for highly nonstationary noise environments. The noise estimate is updated by averaging the noisy speech power spectrum using a time and frequency dependent smoothing factor, which is adjusted based on signal presence probability in subbands. Signal presence is determined by computing the ratio of the noisy speech power spectrum to its local minimum, which is computed by averaging past values of the noisy speech power spectra with a look-ahead factor. The local minimum estimation algorithm adapts very quickly to highly non-stationary noise environments. This was confirmed with formal listening tests that indicated that our noise estimation algorithm when integrated in speech enhancement was preferred over other noise estimation algorithms.

Photon statistics characterization of a single-photon source

Abstract: In a recent experiment, we reported the time-domain intensity noise measurement of a single-photon source relying on single-molecule fluorescence control. In this paper, we present data processing starting from photocount timestamps. The theoretical analytical expression of the time-dependent Mandel parameter Q(T) of an intermittent single-photon source is derived from ON?OFF dynamics. Finally, source intensity noise analysis, using the Mandel parameter, is quantitatively compared with the usual approach relying on the time autocorrelation function, both methods yielding the same molecular dynamical parameters.

Noise and interference reduction in digitized signals

Abstract: A method ( 700, 800, 900 ) and apparatus ( 1000, 1100 ) increase a signal quality by analyzing an input signal and output signals from adaptive filters ( 410, 510, 512, 514 ) associated with predetermined signal plus noise plus interference classifications. An actual signal plus noise plus interference classification of the input signal is determined and one of the output signals or the input signal is selected based on a favorable Signal to Noise Ratio or a Signal to Interference plus Noise Ratio. The output signals from the adaptive filters are weighted based on analysis such as statistical analysis ( 310 ) including quantified auto-regressive analysis, Eigenvalue spread analysis, correlation analysis, feedback analysis, and covariance analysis. The predetermined classifications include various combinations of characteristics associated with the signal and interference components. The adaptive filters include multi-band and single band Adaptive Noise Canceling filters ( 312, 314 ), and multi-band and single band Adaptive Line Enhancing filters ( 316, 318 ).

The Impact of A-weighting Sound Pressure Level Measurements during the Evaluation of Noise Exposure

Abstract: Over the past 50 years, the A-weighted sound pressure level (dBA) has become the predominant measurement used in noise analysis. This is in spite of the fact that many studies have shown that the use of the A-weighting curve underestimates the role low frequency noise plays in loudness, annoyance, and speech intelligibility. The intentional de-emphasizing of low frequency noise content by A-weighting in studies can also lead to a misjudgment of the exposure risk of some physical and psychological effects that have been associated with low frequency noise. As a result of this reliance on dBA measurements, there is a lack of importance placed on minimizing low frequency noise. A review of the history of weighting curves as well as research into the problems associated with dBA measurements will be presented. Also, research relating to the effects of low frequency noise, including increased fatigue, reduced memory efficiency and increased risk of high blood pressure and heart ailments, will be analyzed. The result will show a need to develop and utilize other measures of sound that more accurately represent the potential risk to humans.

Noise adaptation system of speech model, noise adaptation method, and noise adaptation program for speech recognition

Abstract: An object of the present invention is to facilitate dealing with noisy speech with varying SNR and save calculation costs by generating a speech model with a single-tree-structure and using the model for speech recognition Every piece of noise data stored in a noise database is used under every SNR condition to calculate the distance between all noise models with the SNR conditions and the noise-added speech is clustered Based on the result of the clustering, a single-tree-structure model space into which the noise and SNR are integrated is generated (steps S1 to S5) At a noise extraction step (step S6), inputted noisy speech to be recognized is analyzed to extract a feature parameter string and the likelihoods of HMMs are compared one another to select an optimum model from the tree-structure noisy speech model space (step S7) Linear transformation is applied to the selected noisy speech model space so that the likelihood is maximized (step S8)

Full-chip vectorless dynamic power integrity analysis and verification against 100uV/100ps-resolution measurement

Abstract: The advances in semiconductor manufacturing, EDA tools, and VLSI design technologies are enabling circuit designs with increasingly higher speed and density. However, this trend is causing the on-chip power distribution network to experience larger dynamic voltage fluctuations due to dynamic voltage drop, L di/dt noise, and/or LC resonance. As a result, the analysis of power-integrity, as well as the evaluation and calibration of the analysis methodology, has become a major challenge in designing high-performance circuits. An innovative vectorless dynamic power-ground noise analysis approach is discussed in this paper. This approach addresses full-chip complexity with transistor-level accuracy. This analysis approach demonstrated very good correlation with an on-chip supply noise measurement in 0.13-/spl mu/m CMOS technology, capable of achieving 100 /spl mu/V/100 ps resolution.

Device and method for noise suppression

Abstract: PROBLEM TO BE SOLVED: To provide a device and method for noise suppression with which neither musical noise in a noise section nor distortion in a speech section is generated. SOLUTION: Disclosed is the noise suppressing device which suppresses a noise signal in an input signal wherein the noise signal and a target signal are mixed together. The noise suppressing device comprises a noise estimation part 103 which estimates a noise signal component from the input signal, a speech/noise judgement part 108 which judges a target signal section and a noise signal section from the input signal, a noise suppression part 104 which performs noise suppression based upon a 1st suppression coefficient from the input signal and estimated noise signal, a noise excess suppression part 105 which performs noise suppression on the basis of a 2nd suppression coefficient larger than the 1st suppression coefficient from the input signal and estimated noise signal, and a switching part 109 which performs switching between the output signal of the noise suppression part 104 and the output signal of the noise excess suppression part 105 according to the judgement result of a section judgement means. COPYRIGHT: (C)2005,JPO&NCIPI

Technique for bit-accurate comfort noise addition

Abstract: The addition of comfort noise to an image serves to hide compression artifacts. To facilitate comfort noise addition, supplemental information accompanying a video image contains at least one parameter that specifies an attribute regarding comfort noise. Typically, the supplemental information includes parameters that function to turn the comfort noise on and off, as well as to indicate the level of noise to add, based on the expected level of compression artifacts.

Linear current mode imager with low fix pattern noise

Abstract: A new imaging architecture with a linear current mode active pixel sensor (APS) is presented. Focal plane image processing in the current domain includes a correlated double sampling (CDS) unit for fixed pattern noise (FPN) suppression. The CDS unit is composed of a first generation current conveyer circuit and a class AB cascaded current memory cell. A measured FPN of 0.9% from saturation level is achieved with the CDS unit compared to 1.9% FPN from current mode images without noise suppression circuitry. A 40 by 40 imaging array was fabricated in a standard 0.5 /spl mu/m process and its functionality was successfully tested. Theoretical analysis for second order non-linear effects is also presented.