The peak power consumption has become an important concern in the hardware design process of some of today’s applications, such as Energy Harvesting (EH) and Bio-Implantable (BI) electronic devices. The limited peak harvested power in EH devices and heating concerns in BI devices are the main reasons for power control’s importance in these devices. This paper proposes a generalized design approach for ultra-low-power arithmetic circuits. The proposed circuits are based on Residue Number System (RNS) combined with deterministic bit-streams. The resulting circuits can be used in systems with a restricted power budget. We suggest several approaches to design generic hardware-efficient adders, multipliers, multiply-accumulate units (MAC), forward converters (FC), and reverse converters (RC). Using the proposed approach, designing these components for any moduli of the RNS can be performed through simple bit-width adjustments in the circuits. The synthesis results show that the proposed adder achieves, on average, 69% and 2% lower area compared to the bit-serial and a state-of-the-art RNS adder, respectively. Furthermore, the proposed multiplier outperforms the bit-serial, interleaved, and a state-of-the-art design for multiplying RNS numbers by, on average, 57%, 60%, and 77% in terms of power consumption, respectively. The efficiency of our approach is shown via two essential applications, digital signal processing and machine learning. We implement an FFT engine using the proposed method. Compared to prior RNS implementations, our design achieves 47% lower power consumption. We also implement a CNN accelerator’s Processing Element (PE) with the proposed computation elements. Our design provides considerable speedup and lower power consumption compared to a state-of-the-art ultra-lower-power design.