Error correction capability of convolutional codes is improved by increasing code constraint length. However, increasing the constraint length results in high complexity of optimum Viterbi Decoding algorithm because the number of computations in Viterbi algorithm is exponentially proportional to the constraint length. Consequently, Decoding of high constraint length convolutional codes using Viterbi algorithm may practically be impossible. Sub-optimum Decoding algorithms such as Fano and Stack algorithms have been proposed to feasible fast sequential Decoding of high constraint length convolutional codes. In this paper, we introduce different methods of implementing Fano and Stack algorithms and propose some techniques to improve their speed and required memory. We compare the introduced implementations of the algorithms in terms of error correction capability, Decoding time and required memory. Furthermore, we use simulation results to show that if the communication error is low, Fano and Stack algorithms can provide the same error correction capability as the optimum Viterbi algorithm in very short Decoding time.

In this paper, we focus to find desired node position in indoor environments using a sequence of observations and user movement records. For this purpose, we first record the user's movements in indoor environments by defining a set of states and several matrices, which are Viterbi inputs. To record the fingerprints of the environment, we move across the entire coordinates of the building to collect and record the fingerprints of different places. In the online phase, we use the Weighted K-Nearest Neighbors (WKNN) algorithm in parallel to check the accuracy of both WKNN and Viterbi algorithms and to correct the WKNN behavior by Viterbi. During this phase, an experimental node is inserted into the environment and moves in the desired direction by determining the destination. The proposed method calculates the current location of the node and its most probable location in the next step. The results of the implementation and testing of the proposed algorithm in the Faculty of Engineering, Arak University, show the optimal performance of the proposed idea for predicting the location and path of the node.

Viterbi decoder is used for Decoding data encoded using Convolution Forward Error Correction codes or data that suffers from inter-symbol interference. They occur in a large proportion of digital transmission. Viterbi decoders employed in digital wireless communications are complex and dissipate large power. The proposed method focuses on gate diffusion input (GDI) which is a low power technique of digital circuit design. Dynamic component of power is reduced in GDI technique as source of PMOS is not permanently connected to Vdd. It also reduces the latency of the circuit. The Viterbi decoder is implemented using GDI cell with 0.25 mm and 90 nm technology with 2.5 V Vdd. Frequency is varied from 15 MHz to 25 MHz. The outputs of the convolutional encoder designed for the constraint lengths K 4, 5, 6, 7 and rate are fed to the designed Viterbi decoder. The comparison results showed 29% reduction in power consumption and 66% reduction in area by using GDI circuit than the CMOS circuit.

Daghoghi’s story in Masnavi Manavi is one of the stories which bewildered the readers but the bewilderment that the poet has times and times refers to is a mystical bewilderment.The poet’s experience and the theme of the story do not look familiar to the reader and it has hidden secrets whose understanding is not possible with our ordinary senses and it is beyond our everyday life experiences.  The internal ambiguity of most events requires commentaries and interpretations in such a way that in order to unveil its mysteries one cannot rely on logic and intellect. This story is an eternal experience which is transmitted through the unconscious and the key to the discovery of the unconscious is the study of its symbols.  In this article attempt is made to give a brief outline of the story and to solve some of its mysteries and complexities.

The parameters of a Hidden Markov Model (HMM) are transition and emis-sion probabilities. Both can be estimated using the Baum-Welch algorithm. The process of discovering the sequence of hidden states, given the sequence of observations, is performed by the Viterbi algorithm. In both Baum-Welch and Viterbi algorithms, it is assumed that, given the states, the observations are independent from each other. In this paper, we first consider the direct dependency between consecutive observations in the HMM, and then use conditional independence relations in the context of a Bayesian network which is a probabilistic graphical model for generalizing the Baum-Welch and Viterbi algorithms. We compare the performance of the generalized algorithms with the commonly used ones in simulation studies for synthetic data. We finally apply these algorithms on real data sets which are related to biological and inflation data. We show that the generalized Baum-Welch andViterbi algorithms significantly outperform the conventional ones when sample sizes become larger.

Today, there are various statistical models for the discrete simulation of the rainfall occurrence/ nonoccurrence with more emphasizing on long-term climatic statistics. Nevertheless, the accuracy of such models or predictions should be improved in short timescale. In the present paper, it is assumed that the rain falloccurrence/non-occurrence sequences follow a two-layer Hidden Markov Model (HMM) consist of a hiddenlayer (discrete time series of rainfall occurrence and non-occurrence) and an observable layer (weather variables), which is considered as a case study in Khoramabad station during the period of 1961-2005. The Decoding algorithm of Viterbi has been used for simulation of wet/dry sequences. Performance of five weather variables, as the observable variables, including air pressure, vapor pressure, diurnal air temperature, relative humidity and dew point temperature for choosing the best observed variables were evaluated using some measures of error evaluation. Results showed that the variable of diurnal air temperature is the best observablevari able for Decoding process of wet/dry sequences, which detects the strong physical relationship between those variables. Also the Viterbi output was compared with ClimGen and LARS-WG weather generators, in terms of two accuracy measures including similarity of climatic statistics and forecasting skills. Finally, it is concluded that HMM has more skills rather than the other two weather generators in simulation of wet and dry spells. There fore, we recommend the use of HMM instead of two other approaches for generation of wet and drysequences.

Myths and mythical narration have several valences of meaning and as a result their surface and deep-structures can evolve and transform based on the horizon of meaning in every text in each historical period. The narrations of Bibis stories have two structures: an initiation custom of marriage (pagosha) and a religious-based tradition. The myths in the stories of Bibis such as “Bibi Shahr-e Banoo” in Rey and “Bibi Shah Zeinab” in Yazdel region in Kashan, even though originally they may have had the deep-structure of “sacrificing the fairies; ” the recreations of the old narrations and also the form of restructured buildings in the Islamic period can be indicative of the religious experience and its relation to the holy time. Some of the signs of the religious experience and its closeness to the religious matter or at least its tendency towards it are “the quality of being mysterious, ” “feeling of awe, ” and “splendor” which eventually result in the realization of the descriptions of the holy matter. These signs are embodied in the details and structures of the narrations as well as related old constructions.

In this paper the combination of equalization and turbo Decoding is studied. In the iterative Decoding of a product code in block turbo coding system, the equalization process is performed within the iteration loop. This research aims to investigate the decision feedback equalizer (DFE) incorporated in the iterative Decoding. Simulation results show that the more severe channel interference, the more the gain of the combination of DFE and turbo decoder performance compared with the case that using them individually.