Reactive hyperemia has been conventionally quantified using time-do main para meters such as peak hyperemia , time to peak hyperemia and total hyperemic response   . These parameters provide a description of the response but may e xh ibit large inter- and intrasubject variations   . Time to pea k hypere mia is proposed to reveal the vascular resistance  . Total hyperemic response was measured by taking the area under the curve of the hyperemic response. It was evaluated within the time when the blood flow to return to baseline levels a fter pressure released. Total hypere mic response has been suggested since it is considered as a required distribution for metab olic repayment caused by tissue ischemia .
ABSTRACT: In this paper we first analyse the characteristics of FPGA and puts forward fast pulse compression architecture. System-level simulation using MATLAB and Verilog for space borne SAR is carried out by the new way of system verification techniques. In anticipation of much potential joint Space-Based Radar (SBR) missions between the Air Force and NASA in the future. We propose to develop an FPGA-based (field programmable- gated-array) architecture for on-board processing of radar data. In particular, the hardware is targeted for the high computational load in processing Synthetic aperture-radar (SAR).Pulse compression plays an important role in design of the radar system. Pulse compression using linear frequency modulation techniques are very popular in modern radar. The linear frequency modulation is done here to resolve two small targets that are located at long range with very small separation between them. Pulse compression technology is defined as a process that radar transmitter emits large pulse frequency modulation signal and the receiver can obtain narrower pulse after matching and compression processing. The method better resolves the contradiction between the restriction of peak pulse power and range resolution in radar. Pulse compression actually employ matching filter for radar receiving signal. Based on the theory of matching filter, the impulse response of filter is the conjugation of input signal. Similarly Azimuth resolution is carried out by using Azimuth reference function.
The phenomenon of vibrational resonance (VR) in which the response of the system to a weak periodic signal can be enhanced by the application of the high-frequency periodic perturbation of appropriate amplitude. The analysis of VR has received a considerable interest in recent years because of its importance in a wide variety of contexts in science and engineering. For example, Landa and Mc Clintock  have shown that the occurrence of resonant behaviour with respect to a low-frequency force caused by the high-frequency force in a bistable system and later Gitterman  proposed an analytical treatment for this resonance phenomenon. Experimental evidence of the vibrational resonance has been demonstrated in analog simulations of the overdamped duffing oscillator , in an excitable electronic circuit with Chua’s diode  and in a bistable optical cavity laser . It has been thoroughly studied in a large class of dynamical systems such as a monostable system , a multi-stable system [1,2,7], time-delayed systems [8,9], spatially periodic system , small- world networks [11,12], noise-induced structure , biological nonlinear maps [14,15] and coupled oscillators .
The orthogonality allows for efficient modulator and demodulator implementation using the FFT algorithm on the receiver side, and inverse FFT on the sender side. Although the principles and some of the benefits have been known since the 1960s, OFDM is popular for wideband communications today by way of low-cost digital signal processing components that can efficiently calculate the FFT. In OFDM serial input data is converted into parallel input data. After conversion, base band modulation technique is applied such as PSK, QPSK, and QAM etc... After this operation, data converted into frequency domain signal (complex form) IFFT operation converts the frequency domain signal into the time domain signal. This time domain signal is same as that of the OFDM signal.At the receiver side, the original information is added with noise signal. That noise signals removed by simple equalization technique with one tab or two-tab equalizer. Then the FFT operation coverts the time domain signal into the frequency domain signal. After performing these operations, the parallel data is converted into the serial data.
Since the background noise simulation should be suitable for handset terminals and hands-free terminals another experiment was conducted using a desktop hands-free terminal in the same test room. A table was positioned in the test room in front of the artificial head, which was still positioned in the centre of the simulated acoustical field. The hands-free terminal was positioned as described in ITU-T Recommendation P.340 [i.9]. Again the transmitted background noise signal between the original sound field and the simulated sound field are compared. The resulting power density spectra for the transmitted background noise are shown in figure 20. Although the four-loudspeaker arrangement was not reequalized after the table was placed in the room the spectra of the transmitted background noise match rather well. It can be expected that even for desktop hands-free phones placed in the simulation environment the measured performance of background noise transmission is comparable to the one measured in typical office
When de-noising EMG by wavelet threshold de-noising method, the collected noise-containing signal is regarded as a one-dimensional signal model. It can be expressed as: X (t) ＝s (t) ＋n (t), where X(t) is a noisy signal and s(t) is the useful signal, and n(t) is a noise sequence. The basic principle of wavelet threshold de- noising is to use the correlation of wavelet transform. After wavelet transform, the energy of useful signal will be concentrated in a few regions with large wavelet coefficients. Because the wavelet coefficients of the noise are not related to each other, they will be decomposed in various scales, especially in regions with large wavelet coefficients. Therefore, the denoising effect can be achieved by filtering the small wavelet coefficients and retaining the large wavelet coefficients[6-7].
Processing the desired communication signal is the responsibility of the linear path of the receiver and as such it is composed of nominally linear circuit blocks. The LNTA interfaces to the quadrature passive mixers in a capacitive fashion via the capacitors in Fig. 5.19. In reality, each of the four capacitors shown in Fig. 5.19 constitutes two parallel capacitors, each of which goes to one of the two quadrature mixers. In order to isolate the I and Q downconversion chains with minimal voltage swing at the LNTA output, a 1/4-phase passive mixer scheme was used. The noise generated by the transimpedance amplifier (TIA) in a passive mixer system is a well-known problem in cases such as this, where the impedance looking back up into the passive mixer is low . In order to provide a high source impedance to the TIA, it is preceded by a common-gate (CG) buffer, thereby lowering its effective noise contribution. This technique was previously shown in  although the details of the CG buffer in this case were not shown. When placed in parallel with a very large (335pF) differential capacitor, the input impedance of the CG buffer also aids in attenuating the amount of large downconverted blocker that is passed to the remainder of the receiver chain. A second-order active RC biquad (BQ) is utilized to both buffer the TIA and to complete a 3rd-order Chebyshev low-pass anti-aliasing filter. The biquad outputs are designed to drive the discrete ADCs through the ESD network and remain stable over process corner even when loaded with 20pF of capacitance. The 3-dB cutoff frequency of the composite (CG-TIA-BQ) filter is approximately 2.3MHz so as to avoid introducing substantial group delay distortion for desired signals occupying double-sided bandwidths up to 4MHz. Coarse dc offset cancellation is provided by adding a differential static current to the virtual ground nodes of the first biquad OTAs. This allows the receiver to process large baseband IMD products even in the presence of large dc offset.
The resolution is the important parameter of the radar. Here waveform design plays an important role in the radar applications. These waveform designs can be achieved by using signal processing tools like auto correlation and ambiguity function. In this project signal processing techniques have been developed by using above functions. These techniques are most useful in the multi target scenario of the radar. In this project the signals like burst signal, linear frequency modulated (LFM) signals are used for the determination of radar resolution and also these waveforms are implemented in popular codes like “COSTAS”. The three dimensional plots are generated to evaluate both range and Doppler resolution by using ambiguity functions. The results are being presented for the COSTAS code by using LFM signals. The performance of these waveforms is compared with the conventional waveforms.
A simplified ES receiver is presented in Fig. 1. Since the RF amplifier in a satellite communication receiver must generate as little noise as possible, it is called a low noise amplifier (LNA). The mixer and local oscillator form a frequency conversion stage that down-converts the radio frequencysignal to a fixed intermediate frequency (IF), where the signal can be amplified and filtered accurately. BPF is the band pass filter, used for selecting the operational frequency band of the ES. The receiver shown in Fig. 1 employs a single
They provide a joint representation in time and frequency, contrary to the Fourier transform who represents in only frequential form the contained information in signal temporal , from where the disadvantage of loss of events chronology . Wavelets transform takes up same idea as the Fourier transform by adopting a multi-resolution approach: if we look at a signal with a broad window, we will be able to distinguish from the coarse details. In a similar way, increasingly small details could be observed by shortening the window size. Wavelets analysis objective is thus to carry out a kind of adjustable mathematical microscope. In this study, we developed a determination method of instantaneous variation of a speech signal formantic frequencies based on complex continuous wavelet transform. The method principle is the phase exploitation of coefficients transformation for the instantaneous frequency extraction by using an analytical complex continuous wavelet transform. The application of this method to the speech signal is carried out by taking account of the acoustic characteristics of this signal.
Abstract: - Electrocardiography generates signals referred to as Electrocardiographic signals or simply ECG which describes the electrical activities of the heart and is very vital in the clinical monitoring and diagnosis of the health conditions of the human heart. Naturally during acquisition, the ECG signals get distorted by different artifacts such as Baseline Wander, Muscle Contractions, Equipment Artifact, Powerline Interference etc., which must be removed otherwise incorrect information regarding the patient’s heart condition will be conveyed. However, the most significant signal that corrupt the ECG is Powerline Interference. Hence, for correct extraction of the features of the ECG signal there is need to separate the wanted signal from noise caused by these signals that corrupt the ECG. Different types of digital filters can be used to achieve this. In this work, a Modified Triangular Window FIR filter was used for the removal of the 50Hz Powerline interference in the ECG. Using MATLAB The Signal Power before and after filtration using the modified window was determined and compared with that of triangular window and simulation results obtained.
The human ear can hear sounds of frequencies in the range 20 Hz to 20 kHz. However, most sounds we work with only contain frequency content in the range of about 100 Hz to 8 kHz. Lower frequency sounds, such as a tug boat whistle, have more frequency content in the low part of the audio range. Higher frequency sounds, such as bird song or dog whistles, have more content in the upper part of the range.
the free virus and infected cells rebound. The state variable E is the best indicator of the progression toward immune system dominance and can be seen in the lower right box of all the state variables. In Figure 4 we plot in the phase plane of the log of the immune effector versus the log of the virus. Note that in this sort of plot time is an implicit variable with only the two state variables being shown. This plot begins at acute infection and thus relatively low levels of E and V . We can see that the viral load undergoes one increase during infection and four increases during treatment interruptions. It is interesting to see that E decreases during most of the treatment interruption only to increase toward the end of the interruption. Observe that each one of these treatment protocols has treatment interruptions under which the viral load and infected cells rebound, while the number of healthy cells drops. Also note that the frequency with which the control is allowed to vary has a large effect on how long it takes the immune response to be stimulated and for the individual to be transferred to the healthy steady state. When the control is allowed to vary daily the control is largely turned off after 400 days, whereas it is not turned off until approximately 600 days when the control varies every 5 days and 900 days are required when the control is allowed to vary every 10 days. The phase plots in Figure 4 also illustrate the difference in system response when the control is only allowed to vary every 10 days. Note how more interruptions are required and there is a good deal more time where the immune response is declining.
Colour vision discriminates variation in the spectrum of light from changes in brightness, and requires the neural circuitry to compare the signals from at least two spectrally distinct cone photoreceptor classes (Jacobs, 1981). Moreover, colour vision systems seek to discriminate between objects that differ in reflectance, regardless of the lighting conditions. This is achieved by decomposing the colour signal (spectral radiance) arriving at the eye from an object into the spectral reflectance of the object and the spectral irradiance in the environment. Considering the broad absorbance spectra of cone photoreceptors and the limitations they impose on spectral resolution, it was suggested that more than three cone classes may not add enough spectral resolution to outweigh the costs of additional cone classes (Barlow, 1982; Bowmaker, 1983; Maloney, 1986; Chiao et al., 2000b). Why, then, do many reptiles, birds and shallow-water fish use four cone classes (Goldsmith et al., 1981; Goldsmith, 1990; Hawryshyn and Hárosi, 1991; Neumeyer, 1992; Hawryshyn and Hárosi, 1994; Hawryshyn et al., 2003; Sabbah et al., 2010)? Birds and diurnal reptiles often possess coloured oil droplets in their eyes. These screening pigments narrow the spectrum of photoreceptors, and thus render visual systems with four cone classes more efficient (Goldsmith, 1990; Vorobyev, 2003). To date, however, the question of high-dimensional colour vision in shallow-water fish, which lack coloured oil droplets, is still unsolved.
the signalresponse of plain interdigitated electrodes during antigen–antibody conjugation has increased from 260.80 to 736.33 pF when the gold nano parti- cles are coated on the plain interdigitated electrodes. At microfluidic flow condition, the signalresponse of antigen–antibody conjugation in gold nanoparticle- coated interdigitated electrodes is 2.5 times than in plain interdigitated electrodes. At 20 kHz frequency, the signalresponse of plain interdigitated electrodes during antigen–antibody conjugation has increased from 205.85 to 518.48 pF when the gold nano parti- cles are coated on the plain interdigitated electrodes. Based on the measured results, the following conclu- sions can be made. (1) The functionality of the indi- vidual layers in the sensing platform is validated with the measured change in capacitance. (2) The gold nan- oparticle coated interdigitated electrode has higher sensitivity than the plain interdigitated electrode dur- ing the CA-125 antigen antibody interaction. (3) The capacitive sensing signalresponse increased propor- tionally with the increase in concentration of the anti- gens during the antigen–antibody conjugation. (4) The effect of shear on the sensing signalresponse is evident given the lower capacitive signal during antigen–anti- body conjugation in the microfluidic flow condition as compared to the static drop condition. The observed effect of shear stress in the microfluidic flow condition during the antigen–antibody conjugation can be miti- gated by incorporating the following design changes in the sensing platform and microchannel. (i) The sens- ing platform with nano well-structure immobilized the antibody into each well, can reduce the shear effect during the microfluidic flow. (ii) The surface treatment to the microchannel for controlling the hydrophilicity of channel reduce the shear caused by the microfluidic flow significantly and thus the effect of the shear on sensing platform can be controlled. Though our focus was on isothermal microfluidic devices, the future work on evaluating the influence of thermal conditions on the sensing signalresponse in the microfluidic platform would provide additional information regarding the stability of the bioconjugation chemistries in thermocy- cling microfluidic biosensing applications.
Fig. 4 and Fig. 5 show two examples of the tested clean ECG signals. For the ECG signal spectrum in Fig 4., the standard deviation and mean are 43.54 and 15.32, respectively. For Fig. 5, the standard deviation is 68.29 and the mean is 13.86. The trained PSONN gives the cutoff frequency of 14% and 17% for the first and second ECG signals, respectively. For both figures, part (a) is the pseudo-clean signal, (b) is the signal corrupted by random noise and (c) shows the result of FIR filtering with the cutoff calculated by the proposed method using PSONN. Comparing the pseudo-clean and PSONN filtered ECG signals in both figures show that PSONN can very smoothly filter the high frequency noise and has acceptable performance for ECG noise removal.
A peep is a signal wherein the frequency increments ('up- tweet') or diminishes ('down-twitter') with time. Tweet tweak, or straight frequency adjustment utilizes sinusoidal waveforms whose momentary frequency increments or diminishes directly after some time. These waveforms are regularly alluded to as direct peeps or essentially chirps. The rate at which the frequency changes is known as the twitter rate. In double twitter tweak, paired data is transmitted by mapping the bits into trills of inverse peep rates. For example, more than one piece period "1" is allotted a tweet with positive rate an and "0" a peep with negative rate −a. Peeps have been vigorously utilized in radar applications and therefore propelled hotspots for transmission and coordinated channels for reception of straight tweets are accessible. In a straight trill, the prompt frequency f(t ) differs directly with time:
The basic SFR model averages the machine dynamic behaviour in a large system into an equivalent single machine. This approach is to provide the minimum order model that retains the essential average frequencyresponse shape of a system with typical time constants and active speed governing. The simplified model is based on neglecting nonlinearities and allbut the largest time constants in the equations of the generating units of the power system, with assumption that the generation is dominated by the reheat steam turbine generators. This means that the inertia of the generating units and reheat time constants predominate the system average frequencyresponse. The result is a representation of only the average system dynamics, while ignoring the inter-machine oscillations . The dynamic performance of each rotating mass is controlled by a separate governor by integrating the individual accelerating power. A general diagram of an individual power plant is shown in Fig.1
the amplitude of the signal is changed, however the phase is not aected. On contrary, if the same perturbation is injected during the zero crossing, phase changes instantly but the amplitude is not. Thus, it can be seen that the phase noise of the oscillator depends on the time instant when the noise is introduced in the resonator. Hajimiri and Lee proposed the impulse sensitivity function ( ISF for short or Γ(x) ), to represent the described behavior of phase uctuations. It is a dimensionless, amplitude independent and periodic function with period of 2π . It is measured as a relative phase change to a signal period for dierent injection instants of the single test pulse of known amount of electrical charge. The ISF reaches the maximum when the pulse is introduced during zero crossings and equals zero when the perturbation is applied at the peak of oscilla- tions. Once the ISF is derived, it is expanded in terms of a Fourier series with real coecients. These coecients are then used to express the phase noise equation in a logarithmic scale as