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The implemented method for data recovery in some practical code division multiple access (CDMA) systems is the matched filter detector which has zero decision threshold in the symmetric modulations. Because in the multiuser communication systems, the cochannel interference changes the observation noise model to Non- Gaussian one, using zero thresholds is not optimal anymore. In this paper, we obtain the optimal threshold of the matched filter detector in the presence of the block faded interference and fast frequency flat Rayleigh faded desired user signal. We show that the probability of error for this system can be decreased using the obtained optimal threshold. To this end, we derive the analytic probability of error of the communication system with interference which leads to the condition of having an optimal threshold for this system and its value. We have also compared the obtained analytic results with the Monte Carlo simulation curves to validate the derived analytic expressions. [ABSTRACT FROM AUTHOR]

The effect of jammer on radar or jamming performance has been and is being assessed on the basis of range reduction where consistency in tracking target ability is more important than range reduction in a tracking radar. A new criterion known as relative radar functionality destruction time is defined and introduced as the relative of functionality destruction time of radar to one period of jammer, where jammer signal and target echo power are of concern. The effective parameters in relative time of the receiver functioning destruction are assessed. Next, this criterion is applied in the assessment of simple conical scan radar receiver against a conventional jamming (sweep noise jamming). This criterion is modeled and simulated on a search radar in the jamming environment where the minimum required standard deviation of noise for destroying the radar function yields. By implementing the structure of a frequency modulated continuous wave tracking radar structure, a simple target based on digital radio frequency memory method and one type of jamming against this radar in a simultaneous manner, the functionality destruction is extracted for different radar parameters. This new criterion on outperforms its counterparts. [ABSTRACT FROM AUTHOR]

This paper presents a study of hard combination data fusion for cooperative spectrum sensing in Cognitive Radio (CR). Fast and accurate spectrum sensing is crucial in realizing a reliable cognitive network. Cooperative spectrum sensing can help reducing the mean detection time and increasing the agility of the sensing process. However, when the number of cognitive users is large, the bandwidth need for the control channel that are used to report the secondary user nodes' results to the fusion center may become excessively large. This paper presents a hard decision-based cooperative sequential detection scheme to reduce the average sensing time that is required to reach a detection decision. In the scheme, each cognitive radio computes the log likelihood ratio for its every measurement, and quantizes its measurements then sends its hard-decision to base station and the base station sequentially accumulates these log likelihood statistics and determines whether to stop making measurement. [ABSTRACT FROM AUTHOR]

Surface electromyography (SEMG) from respiratory muscles is a non-invasive and effective method of studying neuromuscular diseases, muscle fatigue, enhancement of muscular function and also human-computer interface. This signal is contaminated by different noises. These include environmental noises like power line noise and also internal noises such as electrocardiographic noise. The clean EMG signal can be extremely useful for pathological purposes. In this study, diaphragmatic EMG signals were recorded with Power Lab system from seven subjects. The signals showed contamination due to power line interference (PLI) and also cardiac activity. Adaptive filters were used to reduce cardiac noise as well as 50 Hz (the fundamental) power line noise and its harmonics. Recursive least squares algorithm was used for the structure of the adaptive filter. Different values of the filter parameters; filter order and forgetting factor were examined for the noise removal purpose. Performance of the adaptive filter was quantified by signal-to-noise ratio and coherence measures for simulated data. The results show that we can successfully eliminate PLI and ECG noise from SEMG signals with adaptive filters. The figures and tables obtained help to decide which parameters of the filter are the best for our study. [ABSTRACT FROM AUTHOR]