السیرة النبوية از احمد بن زینی دحلان (م ۱۳۰۴ھ) کے مباحث فقہیہ کا تحقیقی جائزہ

Ahmad bin zeni Dahlan was born in Mecca on 1231 AH. He was a great scholar of Tafseer, Hadith, Fiqh and Sirah. His book "السیرۃالنبویۃ "is a wonderful piece of writing on sirah of Holy Prophet (PBUH). This book has got a significant place in sirah literature. In this book, Author discusses almost all the aspects of the life of Prophet Muhammad (PBUH), like his attributes, miracles, incidents and battles etc. One of zeni dahlan’s modes of sirah writing is that he derives juristic implications and lessons from the events of sirah which can be called Fiqh al sirah in modern terminology. This article intends to explore the mode of Fiqh al sirah in respect with “Al sirah al nabawiyyah” written by Ahmad bin Zeni Dahlan.

Neuromorphic Hardware Design

In this thesis, a novel technique to embed synaptic plasticity in neuromorphic hardware is proposed named as Frequency Dependent Synaptic Plasticity. This technique provides an alternate interpretation for plasticity which was conventionally modeled as weight value. In the proposed model of neuromorphic hardware, plasticity is implemented in frequency domain by considering a synaptic connection performing bandpass filtering operation. Currently most of the neuromorphic hardware are based on time domain based plasticity techniques. The proposed model attempts to contribute and suggest an out of the box solution for neurocomputational applications. It has been established through this thesis that the proposed model is biologically plausible in terms of implementation of different phenomena observed in a biological brain such as rate-encoding by Class I type of neuron, decoding of rate-encoded information by selective triggering at post synaptic side, resonance aware synaptic plasticity, population coding, role and interpretation of tuning curve, and frequency based neuronal communication. The proposed hardware operates in analog domain which is closer to the operational domain of brain as compared to its digital counterpart. This thesis also proposes a novel architecture to embed population coding on neuromorphic hardware. Further, it is explained in this thesis that a synaptic junction based on proposed model has a non linear transfer function which omits the requirement of hidden layer in classifying non-linear problems. This will allow applications to use least possible resources, employing input and output nodes only, as compared to a network based on linear weight values.