This paper proposes a general intelligent video surveillance monitoring system to explore and examine some problems in animal behavior analysis particularly in cow behaviors. In this concern, farmers, animal health professionals and researchers have well recognized that analysis of changes in the behavioral patterns of cattle is an important factor for an animal health and welfare management system. Also, in today dairy world, farm sizes are growing larger and larger, as a result the attention time limits for individual animals smaller and smaller.
Preview Kb Abstract One of the major practical problems in digital communication systems is channel distortion which causes errors due to intersymbol interference.
Since the source signal is in general broadband, the various frequency components experience different steady state amplitude and phase changes as they pass through the channel, causing distortion in the received message. This distortion translates into errors in the received sequence.
Our problem as communication engineers is to restore the transmitted sequence or, equivalently, to identify the inverse of the channel, given the observed sequence at the channel output.
This task is accomplished by adaptive equalizers. Typically, adaptive equalizers used in digital communications require an initial training period, during which a known data sequence is transmitted.
A replica of this sequence is made available at the receiver in proper synchronism with the transmitter, thereby making it possible for adjustments to be made to the equalizer coefficients in accordance with the adaptive filtering algorithm employed in the equalizer design.
When the training is completed, the equalizer is switched to its decision directed mode.
Decision feedback equalizers are used extensively in practical communication systems. They are more powerful than linear equalizers especially for severe inter-symbol interference ISI channels without as much noise enhancement as the linear equalizers.
This thesis addresses the problem of adaptive channel equalization in environments where the interfering noise exhibits Gaussian behavior. Advantages and problems of this system are discussed and its results are then compared with DFE using multi layer perceptron net MLP.
Results indicate that the implemented system outperforms both the least-mean square LMS algorithm and MLP, given the same signal-to-noise ratio as it offers minimum mean square error.
The learning rate of the implemented system is also faster than both LMS and the multilayered case.Courses offered in the Certificate, Master’s and PhD programs in Engineering are one-term four-credit courses unless otherwise specified. Not all courses are offered each year. Equalization is the reversal of disturbance that is present in the signal.
The device that reverses the noise in the signal that is transmitting through a medium is known as equalizer. As because of the multipath channel fading effect occurs and due to this transmitted signal become weak. Alptekin PAMUK May on channel equalization is given and simulations are provided to compare them As a novel contribution, the thesis proposes two new equalization methods by amending existing algorithms and shows that these modi ed algorithms im-prove the state-of-the-art in channel equalization in terms of complexity .
application, “Adaptive channel equalization”, has been discussed in this thesis. In this chapter, we will discuss the need for channel equalization by considering the problem of Intersymbol-interference (ISI) in digital communication systems.
of the radio transmission channel and the need for multiuser applications call for multicarrier modulation schemes, which are the subject of this thesis. oTday the Orthogonal requencyF Division Multiplexing (OFDM) modulation scheme is the most widespread technique for high-speed wireless data transmission.
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