Adaptive Least Error Rate

Cystoscopy Image Classication Using Deep Convolutional Neural Networks

In the past three decades, the use of smart methods in medical diagnostic systems has attractedthe attention of many researchers. However, no smart activity has been provided in the eld ofmedical image processing for diagnosis of bladder cancer through cystoscopy images despite the highprevalence in the world. In this paper, two well-known convolutional neural networks (CNNs) ...

The Wavelet Transform-Domain LMS Adaptive Filter Algorithm with Variable Step-Size

The wavelet transform-domain least-mean square (WTDLMS) algorithm uses the self-orthogonalizing technique to improve the convergence performance of LMS. In WTDLMS algorithm, the trade-off between the steady-state error and the convergence rate is obtained by the fixed step-size. In this paper, the WTDLMS adaptive algorithm with variable step-size (VSS) is established. The step-size in each subf...

Recursive Least Squares Adaptive Filter a better ISI Compensator

Inter-symbol interference if not taken care off may cause severe error at the receiver and the detection of signal becomes difficult. An adaptive equalizer employing Recursive Least Squares algorithm can be a good compensation for the ISI problem. In this paper performance of communication link in presence of Least Mean Square and Recursive Least Squares equalizer algorithm is analyzed. A Model...

Adaptive Space-Time Equalisation for Multiple-Antenna Assisted Multiple-Input Multiple-Output Systems

This paper investigates an adaptive space-time equalisation (STE) assisted multiuser detection scheme for multiple-antenna aided multiuser systems. A minimum bit error rate (MBER) design is compared with the standard minimum mean square error (MMSE) design. It is shown that the MBER design provides significant performance enhancement, in terms of achievable system bit error rate, over the MMSE ...

Performance Analysis of Acoustic Echo Cancellation Techniques

Mainly, the adaptive filters are implemented in time domain which works efficiently in most of the applications. But in many applications the impulse response becomes too large, which increases the complexity of the adaptive filter beyond a level where it can no longer be implemented efficiently in time domain. An example of where this can happen would be acoustic echo cancellation (AEC) applic...

Least Bit Error Rate Adaptive