Acoustic analysis of infant vocalizations has typically employed traditional acoustic measures drawn from adult speech acoustics, such as f(0), duration, formant frequencies, amplitude, and pitch perturbation. Here an alternative and complementary method is proposed in which data-derived spectrographic features are central. 1-s-long spectrograms of vocalizations produced by six infants recorded...

The nearest-neighbor multilayer perceptron (NN-MLP) is a single-hidden-layer network suitable for pattern recognition. To design an NN-MLP efficiently, this paper proposes a new evolutionary algorithm consisting of four basic operations: recognition, remembrance, reduction, and review. Experimental results show that this algorithm can produce the smallest or nearly smallest networks from random...

-It is widely believed that the back propagation algorithm in neural networks, for tasks such as pattern classification, overcomes the limitations of the perceptron. We construct several counterexamples to this belief. We also construct linearly separable examples which have a unique minimum which fails to separate two families of vectors, and a simple example with four two-dimensional vectors ...

We propose anti-spam filtering methods for agglutinative languages in general and for Turkish in particular. The methods are dynamic and are based on Artificial Neural Networks (ANN) and Bayesian Networks. The developed algorithms are user-specific and adapt themselves with the characteristics of the incoming e-mails. The algorithms have two main components. The first one deals with the morphol...

This paper presents an FPGA implementation of a 3-layer perceptron using the FDFM (Few DSP blocks and Few block RAMs) approach implemented in the Xilinx Virtex-6 family FPGA. In the FDFM approach, multiple processor cores with few DSP slices and few block RAMs are used. We have implemented 150 processor cores for perceptrons in a Xilinx Virtex-6 family FPGA XC6VLX240T-FF1156. The implementation...

There is considered an image recognition problem, defined for the single hidden layer perceptron, fed with 5-by-7 monochrome images on its input under Gaussian noise of their distortion. In this neural network the hidden layer neuron number should be set optimally to maximize its productivity. For minimizing traintime duration and recognition error rate both simultaneously there are suggested t...

optical coherence tomography (oct) uses the spatial and temporal coherence properties of optical waves backscattered from a tissue sample to form an image. an inherent characteristic of coherent imaging is the presence of speckle noise. in this study we use a new ensemble framework which is a combination of several multi-layer perceptron (mlp) neural networks to denoise oct images. the noise is...

We show that a randomly selected N-tuple x of points ofRn with probability> 0 is such that any multi-layer percept ron with the first hidden layer composed of hi threshold logic units can implement exactly 2 2:~~~ ( Nil) different dichotomies of x. If N > hin then such a perceptron must have all units of the first hidden layer fully connected to inputs. This implies the maximal capacities (in t...

The Perceptron i s an adaptive linear combiner that has its output quantized to one o f two possible discrete values, and i t is the basic component of multilayer, feedforward neural networks. The leastmean-square (LMS) adaptive algorithm adjusts the internal weights to train the network to perform some desired function, such as pattern recognition. In this paper, we present an analysis o f the...