A new nonlinear equalizer for high-density magnetic recording channels is presented. It has a structure of the decision-feedback equalizer (DFE) with a nonlinear model at the feedback section and a dynamic threshold detector. The feedback nonlinear model is a sequence of look-up tables (LUTs) indexed by time, and each table is addressed by a transition pattern formed by one future and /spl nu/ past transitions. We call this new nonlinear equalizer the pattern-dependent DFE (PDFE). The feedback nonlinear model cancels the trailing nonlinear intersymbol interference (ISI), and then the data decision is made by considering the precursor nonlinear ISI caused by one future symbol. We propose a tap optimization criterion SNR/sub d/ for the PDFE which in effect tries to maximize the output signal to noise ratio, and derive a closed-form solution for the tap values. We compare the detection performance of PDFE with that of the DFE and the RAM-DFE on experimental channels. The RAM-DFE is a DFE with one large LUT at its feedback section. The results show that the PDFE yields a significant performance improvement over the DFE and the RAM-DFE. Also the PDFE derived in this paper achieves a superior performance compared with the PDFE derived by the minimum mean-square-error criterion.

Since the received signal levels in mobile communications are unknown and the location is varying, acquisition schemes for pseudonoise (PN) sequences with fixed thresholds cannot provide satisfactory performance. This fixed-threshold scheme may cause too many false alarms or result in a low detection probability for a selected threshold value. We present an adaptive acquisition scheme for PN sequences which estimate the background power level, multiply it with a threshold coefficient to keep the false alarms constant, and use it as a threshold.

The transmission of spectral information consumes a large portion of total bit rate in medium-to-low bit rate speech coding. The conventional coding methods of LSP parameters generate redundant spectral information or spectral distortion by the fixed update rate of LSP parameters independent of the order of coefficients and phonetic context. We propose a multiple type frame segmentation (MTFS) method which allows various types of two-dimensional segmentation of speech frames to save the transmission rate of the LSP parameters without increasing the spectral distortion. The intra-frame spectral distortion (IFSD) is defined to measure the spectral distortion of the reconstructed spectrum. The proposed method generates a less distorted spectrum with fewer bits compared with the conventional single type frame segmentation (STFS) method.

implement Korean This paper describes a way of neural hardware implementation with the analog-digital mixed mode neural chip. The full custom neural VLSI of Universally Reconstructible Artificial Neural network (URAN) is used system. A to multi-layer perceptron with is trained successfully under the limited accuracy in computations. The network with a large frame input layer is tested to recognize spoken korean words at a forward retrieval. Multichip hardware module is suggested with eight chips or more for the extended performance and capacity.

A continuous-time Markov chain model for an asynchronous spread spectrum packet radio network is presented. The network consists of N fully connected nodes, and the radios in all nodes are identical. Packets arrive at each node and are retransmitted when lost, both according to Poisson processes with different rates, and packet lengths are exponential in distribution. A simple threshold approximation is used to account for the multiuser interference, and the preamble collision probability at receiving radios to account for the capture effect. The approximate analysis gives good results in most cases, and overestimates the throughput when packets are frequently lost on account of the multiuser interference or the preamble collisions. The network stability conditions are discussed and the bistable behavior of the network is demonstrated. Results show the effects on throughput and packet delay performance of the network according to the variations of the network size, the packet transmission rate, the preamble collision probability at receiving radios, and the threshold value of the radio channel.>