Development of Earphone with Variable Frequency Filter

This study was designed to explore the effect on speech comprehension of combining two types of signal distortion. A tape of clearly-enunciated sentences in quiet was distorted in each of four ways: low-pass (LP) filtering, time compression, interruption, and noise masking. Data are reported on a population of normal-hearing young men for multiple-choice answer tests of colloquial sentences of either LP filtered at 1, 2, 3, or 4 kHz, time compressed by computer at 250 words/min, interrupted (50 msec on--50 msec off), masked by speech-spectrum noise at +2 dB S/N, or given each of the 12 possible combinations of LP filtering plus the other three distortions. Individual distortion conditions were adjusted to reduce speech comprehension performance to about 90% accuracy, Low-pass filtering above 1 kHz reduced comprehension by no more than five to 10 percentage points, but when LP filtering was added to the other distortions in turn, latent effects were uncovered. The reduction in comprehension with the combined distortions was much greater than the simple additive effects of the distortion and LP filtering by themselves. For example, LP filtering above 2 kHz produced no measurable effect on sentence comprehension but this same distortion in combination with noise masking reduced performance from 89.4 to 59.7% correct (where 25% was chance). This study further validates the multiply-compounded nature of simultaneous types of distortion. The use of LP filtering extends the multiplicative principle to the simulated case of high-frequency hearing losses.

The difference in poststimulus suppression between residual inhibition and forward masking.

The aim of this study is to evaluate the filtering techniques which can remove the noise involved in the time series. For this, Logistic series which is chaotic series and radar rainfall series are used for the evaluation of low-pass filter (LF) and Kalman filter (KF). The noise is added to Logistic series by considering noise level and the noise added series is filtered by LF and KF for the noise reduction. The analysis for the evaluation of LF and KF techniques is performed by the correlation coefficient, standard error, the attractor, and the BDS statistic from chaos theory. The analysis result for Logistic series clearly showed that KF is better tool than LF for removing the noise. Also, we used the radar rainfall series for evaluating the noise reduction capabilities of LF and KF. In this case, it was difficult to distinguish which filtering technique is better way for noise reduction when the typical statistics such as correlation coefficient and standard error were used. However, when the attractor and the BDS statistic were used for evaluating LF and KF, we could clearly identify that KF is better than LF.

Emergent explosive transition on ring networks with low-pass filter

Digital filters with variable bandwidth can be used for a variety of applications. Arbitrary change in the bandwidth of a digital Finite Impulse Response (FIR) filter can be acquired using sampling rate converters. In this paper, a sampling rate converter is proposed which is generated from Pascal structure, a fractional delay filter having low hardware complexity and high modularity. The proposed sampling rate converter requires lesser number of multipliers for implementation when compared with the sampling rate converters in the literature. A low pass filter having a single bandwidth sandwiched between two sampling rate converters can contribute multiple bandwidths in such a way that each bandwidth is an arbitrary variation of the original bandwidth. A two stage Frequency response masking approach (FRM) is used for the hardware efficient design of the original low pass filter. A low complexity and high modularity novel design for a continuously varying bandwidth of a digital FIR filter is proposed in this paper using the proposed sampling rate converter. The modularity of the Pascal structure can be used to control both pass band ripple as well as stop band attenuation of the continuously variable bandwidth FIR filter design. Different communication standards in a Software defined radio (SDR) channelizer is realized using the proposed design of continuously variable bandwidth filter.

Purpose The purpose of this paper is to introduce modified in–phase and quadrature components (I–Q) demodulator based on low temperature co-fired ceramics (LTCC) dielectric substrate GreenTape 951PX for M-Sequence ultra-wide band (UWB) sensor system. Design/methodology/approach Microstrip low pass (LP) and band pass (BP) filters for UWB sensor systems with required properties (for both filters, minimum attenuation is −40dB in stopband, bandwidth of pass band is 6 to 8.5 GHz for BP filter and cutoff frequency is 2.5 GHz for LP filter) were designed, simulated, fabricated and measured using dielectric substrates Du Pont GreenTape 951 PX. The developed microstrip filters were integrated with all parts of I–Q demodulator on one multilayer structure based on LTCC substrate Du Pont GreenTape 951 PX. Findings Both type of microstrip filters integrated in the I– Q demodulator achieved better transmission characteristics in comparison with commercial available filters. It was shown that LTCC technology based on GreenTape 951PX proves good stability in gigahertz frequency and suitability for fabrication of I–Q demodulator with a multilayer approach. Originality/value The novelty of this work lies in substituting commercially available LP and BP filters used in I– Q demodulator by microstrip LP and BP filters with better performance and furthermore the I– Q demodulator is fabricated based on LTCC instead of previously used PCB.

Our previous work has shown that a three-channel (3-channel) variable filter-bank (VFB) can be successfully applied for compensating various hearing loss patterns (audiograms) with high-accuracy. The 3-channel VFB consists of variable lowpass, variable bandpass, and variable highpass digital filters that are transformed from a normalized analog prototype Chebyshev type-I lowpass filter. Since both the magnitudes (gains) and band edge frequencies of the three variable digital filters are independently adjustable, the 3-channel VFB is considerably flexible for achieving high-accuracy audiogram fitting. The objective of this paper is to reveal and theoretically prove the numerator coefficient-symmetries of the three variable filters, and show that each variable filter requires only one multiplication for its numerator filtering operations, so the total number of multiplications can be significantly reduced, which facilitates high-speed audiogram fitting and low-power implementation.

This paper proposes a switch open fault detection method for a dual three-phase inverter system by using the DC-link current ripple analysis in an asymmetric six-phase permanent magnet synchronous motor (PMSM). When a switch open fault occurs, specific ripple components appear in the DC-link current at either the fundamental or double the fundamental frequency, depending on the type of open fault. To extract these ripple components, the proposed method applies a variable high-pass filter (VHPF), followed by a variable all-pass filter (VAPF) to introduce a 90-degree phase shift and enable peak value estimation. A low-pass filter (LPF) is then used to suppress high-frequency noise, and correlation analysis with phase current signals is conducted to detect the fault. The proposed algorithm requires no additional hardware and has been experimentally validated using a propeller benchmark system. The experimental results demonstrate its effectiveness in identifying not only the occurrence of faults but also the specific faulty phase.

In the introduction of this paper are briefly presented the most important sources of noise in data acquisition modules and classical techniques for reducing this noise. Are clarified the types of input configurations available on data acquisition devices and are explained how should be choused and used the best configuration for an application. Also are analyzed the interference noise pick up mechanisms and the methods to minimize interference noise by proper cabling and shielding. After that it is described a new method of noise reduction, in which a square-wave signal is modulated with signal from sensor (input signal) and then it is applied at instrumentation amplifier. The amplified signal is modulated again with the same signal type before analog to digital conversion. The noise and offset voltage that appears due amplifier and from external sources are modulated only once by the final multiplier and translated to the harmonics. By using a low-pass filter, results a clear output signal with reduced noise components. Further low pass filtering it is necessary for eliminating the residual offset voltages that appears due to the use of this technique.

This paper aims at verifying if the number of muscle synergies is influenced by the filtering process. Firstly, EMG activity of 12 muscles of the lower limb of a healthy subject was recorded during walking trial. Then, the Wavelet-Independent Component Analysis was used for the separation of the EMG, considered as reference signal, and the noise source from the raw experimental data. To test the effect of different order and cut-off frequencies of the high-pass and low-pass filtering on the numbers of muscle synergies, a Monte Carlo simulation was performed on the EMG signals. In particular, a dataset of 105 raw EMG signals were generated by adding different noise signals to the reference signal. The reference dataset was pre-processed with different combination of order and cut-off frequency of low-pass filter for the envelope extraction. The simulated dataset, instead, was pre-processed with different combinations of high and low pass filtering. A non-negative matrix factorization was performed to extract the muscle synergies on both the reference dataset and the simulated ones. For each filtering combination, the percentage of the Number of Synergies NoS within each simulated dataset was computed and compared with the NoS obtained from the reference dataset. The reference dataset produced a number of synergies equal to 4 for all the combinations of the tested low-pass filters, proving that, for the EMG signal without artifact, the number of muscle synergies is robust with respect to different low-pass filtering parameters. Conversely, the simulated dataset generated different numbers of synergies in different filtering conditions, ranging from 3 to 5. However, some particular combinations of filtering parameters produced no variation on Nos. Our results demonstrate the importance of choosing the most appropriate filtering parameters, as it resulted that low order and cut-off frequencies lead to an underestimation of the number of synergies, while high orders and cut-off frequencies cause an overestimation of the number of muscle synergies. In this vein, the present paper offers guidelines for the choice of the best filtering condition in muscle synergy evaluation.

In this paper, four different signal processing algorithms which can be applied to reduce the noise from a MEMS-gyroscope-based computer head mouse are presented. MEMS-gyroscopes are small, light, cheap and widely used in many electrical products. MultiPos, a MEMS-gyroscope-based computer head mouse system was designed for persons with movement disorders. Noise such as physiological tremor and electrical noise is a common problem for the MultiPos system. In this study four different signal processing algorithms were applied and evaluated by simulation in MATLAB and implementation in a dsPIC, with aim to minimize the noise in MultiPos. The algorithms were low-pass filter, Least Mean Square (LMS) algorithm, Kalman filter and Weighted Fourier Linear Combiner (WFLC) algorithm. Comparisons and system tests show that these signal processing algorithms can be used to improve the MultiPos system. The WFLC algorithm was found the best method for noise reduction in the application of a MEMS-gyroscope-based head mouse.

ABSTRACTA low noise, high gain, stable radiometer front-end is presented for non-invasive tissue thermometry using custom designed narrow band low noise amplifiers (LNAs) and band pass filter (BPF) with 1.3 GHz centre frequency and − 20 dB pass band of 332 MHz. The fabricated LNAs have >15 dB gain, unconditional gain stability and noise figure (NF) < 1.45 dB in the pass band. The maximum insertion loss of the BPF is <1 dB over 1.2–1.4 GHz with 50 dB suppression in the surrounding communication bands. The cascaded radiometer front-end has measured gain of 45–50 dB, NF < 1.75 dB in the pass band and > 30 dB suppression in the adjacent personal communication bands. The Allan deviation of the total power radiometer indicates long term system stability and presence of Gaussian thermal noise for integration time, . Radiometer measurements of a matched load at room temperature for indicate acceptably low influence of external electromagnetic interference (EMI) and system noise equivalent temperature of 145 K. The brightness temperature measured by the total power radiometer using a resonant slot antenna demonstrates the ability to detect a 0.3°C change in the test load temperature with better than 0.1°C accuracy.

In this article, a well‐defined tunable lowpass‐bandpass (LP‐BP) diplexer with proper performance is provided using stepped impedance lines and square‐looped resonators for telecommunication applications. Our proposed scheme is the first tunable LP filter BP filter diplexer that provides good results. The proposed diplexer has the ability to adjust the cut‐off frequency of the lowpass filter (LPF) and to adjust the center frequency of the bandpass filter (BPF). The varactor diodes in reverse bias were used to make the proposed diplexer tunable. The tuning range of the cut‐off frequency for the LPF is from 0.46 to 0.96 GHz. An important feature of the LPF is a high suppression factor of about 45 dB in the stopband and a sharp roll‐off rate (ROF). The adjustability of the BPF part for the first channel ranges from 1.8 to 2.4 GHz; for the second channel, the ranges from 2.8 to 3.2 GHz, and for the third channel, the ranges from 5.2 to 5.6 GHz. The proposed diplexer is designed, simulated, fabricated, and finally tested and measured. The isolation between the output ports is about 34 dB. Simulation results are in good agreement with the test results and the measured values.

This paper describes the design of variable FIR filters which have magnitude and group delay flatness at /spl omega/ = 0, and have zeros at /spl omega/ = /spl pi/. The filter coefficients are given by multidimensional polynomials of variable parameters to specify variable frequency characteristics, and optimal polynomial coefficients are obtained by minimizing squared error function subject to flat magnitude and group delay constraints. The flatness conditions are transformed so as to be satisfied irrespective of variable parameters. Because the derived conditions are given as simple equality constraints, the optimal polynomial coefficients can be easily obtained. A numerical example is given to show the validity of the proposed technique.

We report on the successful fabrication and demonstration of a low loss, high performance reconfigurable bandpass filter technology. A digitally reconfigurable bandpass filter was implemented by placing the low pass and high pass reconfigurable filters in series. Reconfigurable low pass and high pass filters were implemented by combining MMICs with RF switches selecting capacitor values and off chip high Q fixed inductors. The same circuitry was implemented in both a commercial GaAs pHEMT process as well as Northrop Grumman’s GaN based SLCFET technology. The resulting reconfigurable bandpass filter operates between 1.0-2.0 GHz, with over 500 different filters selections and supporting variable center frequencies as well as variable bandwidth sizes ranging from 70 MHz to 100 MHz, all in a single device. Depending on the center frequency and bandwidth of the selected path, the SLCFET based switched reconfigurable filters demonstrated a NF and insertion loss improvement over the GaAs variant by > 2 dB, while demonstrating an P1dB <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">average</inf> of 33.6 dBm, compared to an average P1dB <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">average</inf> = 17.8 dBm power handling of the GaAs reconfigurable filter. The SLCFET based filter was measured as having 20x greater linearity than the GaAs filter, with the average two tone IIP3 for the SLCFET filter at 43 dBm, compared to 30 dBm for the GaAs design.