Optimising the signal-to-noise ratio
نویسندگان
چکیده
A long-term aim of current research into the frequency assignment problem is to identify features that would enable us to classify instances of the problem in terms of certain easily-computed parameters. Although there are good mathematical reasons why this may be impossible in full generality, experimental evidence is emerging which suggests that instances which occur in practice may be amenable to such classiication 1]. One parameter that contributes to the speciication of an instance of the problem is the signal-to-noise ratio (SNR). Recently some experimental work 2] has been done on the question of nding the minimum SNR for randomly-generated arrays of transmitters. The results suggest that, for a given connguration, the minima occur on the boundaries of what is known as the Voronoi partition. When the number of transmitters is small, and they are 'regularly-spaced', it is intuitively clear that a result of this kind should hold. But it is possible to conceive conngurations in which one powerful transmitter causes complex variations in the SNR within the neighbourhood of a cluster of less powerful transmitters. The question is further complicated by the practical diiculty of specifying an exact propagation law for radio waves under operational conditions. In this paper we shall state general conditions under which it can be proved that the minima of the signal-to-noise ratio must lie on the boundaries of the Voronoi partition. This result is signiicant for two reasons. 1. The complexity of calculating the minimum in any speciic instance is reduced by an order of magnitude.
منابع مشابه
Using a novel method for random noise reduction of seismic records
Random or incoherent noise is an important type of seismic noise, which can seriously affect the quality of the data. Therefore, decreasing the level of this category of noises is necessary for increasing the signal-to-noise ratio (SNR) of seismic records. Random noises and other events overlap each other in time domain, which makes it difficult to attenuate them from seismic records. In this r...
متن کاملRemoving ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique
Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful.Objective: Removing electrocardiogram contamination from electromyogram signals.Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and e...
متن کاملSecrecy of Communications in Data Transmission by Impulses with Unknown Moments of Appearance and Disappearance
We carried out a comparative analysis of the algorithms for detecting a rectangular impulse against Gaussian white noise under either authorized or unauthorized access to the transmitted data. We presupposed that for data transmission the binary communication system is used and that the useful information in the data is whether the signal is present or absent. The case is that unauthorized acce...
متن کاملEffect of signal to noise ratio on the speech perception ability of older adults
Background: Speech perception ability depends on auditory and extra-auditory elements. The signal-to-noise ratio (SNR) is an extra-auditory element that has an effect on the ability to normally follow speech and maintain a conversation. Speech in noise perception difficulty is a common complaint of the elderly. In this study, the importance of SNR magnitude as an extra-auditory effect on speech...
متن کاملAdaptive Filtering Strategy to Remove Noise from ECG Signals Using Wavelet Transform and Deep Learning
Introduction: Electrocardiogram (ECG) is a method to measure the electrical activity of the heart which is performed by placing electrodes on the surface of the body. Physicians use observation tools to detect and diagnose heart diseases, the same is performed on ECG signals by cardiologists. In particular, heart diseases are recognized by examining the graphic representation of heart signals w...
متن کاملAdaptive Filtering Strategy to Remove Noise from ECG Signals Using Wavelet Transform and Deep Learning
Introduction: Electrocardiogram (ECG) is a method to measure the electrical activity of the heart which is performed by placing electrodes on the surface of the body. Physicians use observation tools to detect and diagnose heart diseases, the same is performed on ECG signals by cardiologists. In particular, heart diseases are recognized by examining the graphic representation of heart signals w...
متن کامل